NeurIPS 2024 Career Website
Here we highlight career opportunities submitted by our Exhibitors, and other top industry, academic, and non-profit leaders. We would like to thank each of our exhibitors for supporting NeurIPS 2024. Opportunities can be sorted by job category, location, and filtered by any other field using the search box. For information on how to post an opportunity, please visit the help page, linked in the navigation bar above.
Cambridge-MA (Boston)
We are looking for ML Scientists/Engineers, interns (PhD level) and experts in Molecular Dynamics to join our team at Flagship Pioneering and build the next generation of biotech companies. We are in person at NeurIPS, please contact oviessmann@flagshippioneering.com (Olivia Viessmann) to meet up and chat about roles.
Specific Job Posts:
- Principal Scientist in Molecular Dynamics: Apply here
- Senior ML Scientist/Engineer, Biomolecular Design (All-atom ML modeling): Apply here
- ML Research Scientist Internship, Summer 2025: Apply here
- Senior Computational Scientist, Protein Design: Apply here
- Senior Computational Scientist, Small Molecule Design: Apply here
About Flagship
Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.
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Vector Research Internships Toronto, ON, CA or remote Summer 2025
Description
Work alongside Vector Faculty Members & top AI researchers who are pushing the boundaries of machine learning and deep learning in critical areas such as:
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Computer Vision
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Generative Models
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Health – computational biology, genomics
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Natural Language Processing
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Optimization
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Reinforcement Learning & Representation Learning
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Statistical Learning Theory
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Sequential Decision Making
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Security, Privacy & Fairness
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Quantum Computing
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Robotics
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Machine Learning, Deep Learning
Our renowned research community is pioneering AI breakthroughs, from quantum computing for climate change to 3D machine learning models. Vector researchers are unlocking innovative ways to enhance economics, health, and society with AI.
Research internships are paid positions. They may be remote or in person, in Toronto, Ontario, Canada.
ABOUT VECTOR
The Vector Institute is a leader in the transformative field of artificial intelligence, excelling in machine and deep learning — an area of scientific, academic, and commercial endeavour that will shape our world over the next generation.
Vector has created a community of premier AI talent by attracting and retaining top machine learning and deep learning researchers.
REQUIREMENTS
Research internships may be offered to individuals who meet the following criteria:
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You are in the second year or higher, studying at a university or college
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You are studying in a STEM program (Science, Technology/Computer Science, Engineering, Math) or adjacent disciplines such as Business, Economics or Life Sciences at the undergraduate, master’s or PhD level
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You have completed an Introduction to Machine Learning Course.
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Haven’t taken Intro to ML? Think about the knowledge you possess and how you can apply that to work with a Vector Faculty member!
Please note that current graduate students or postdoctoral fellows of Vector Faculty Members are not eligible for research internships. Questions about Vector’s internship programs? Email us at internships@vectorinstitute.ai
HOW TO APPLY
To apply to Vector’s Research Internship program please fill out our application form. Before you start your application, make sure you have all your documents ready and that you meet the eligibility requirements. If you will be submitting letters of recommendation, make sure to have your Referee’s names and emails ready. Application requirements:
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CV;
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University transcripts (official or unofficial if ongoing term not yet completed) or offer letter;
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Research Statement (optional for undergraduate students); and
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Two letters of recommendation (Required for PhD and postdoc applicants, optional for undergraduate and Masters students).
The deadline for Summer 2025 internship applications is January 13, 2025 at 1:00 PM ET
Vector research internships are paid positions.
Please visit https://vectorinstitute.ai/programs/research-internships/ for more information on the Vector Research Internship Program.
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Seattle, WA
Are you a graduate student passionate about Automated Reasoning and its real-world applications? Join our team of innovators and embark on a journey to revolutionize cloud computing through cutting-edge automated reasoning techniques.Our tools are called billions of times daily, powering the backbone of Amazon's products and services. We are changing the way computer systems are developed and operated, raising the bar for security, durability, availability, and quality.
As an Applied Science Intern, you'll have the opportunity to work alongside our brilliant scientists and contribute to groundbreaking projects. From distributed proof search and SAT/SMT solvers to program analysis, synthesis, and verification, you'll tackle complex challenges at the intersection of theory and practice, driving innovation and delivering tangible value to our customers.
This internship is not just about executing tasks – you'll explore novel approaches to solving intricate automated reasoning problems. You'll dive deep into cutting-edge research, leveraging your expertise to develop innovative solutions. You'll work on deploying your solutions into production, witnessing the real-world impact of your contributions.
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment.
Join us and be part of a team that is shaping the future of cloud computing through the power of Automated Reasoning. Apply now and unlock your potential!
Amazon has positions available for Automated Reasoning Applied Science Internships in, but not limited to, Arlington, VA; Boston, MA; Cupertino, CA; Minneapolis, MN; New York, NY; Portland, OR; Santa Clara, CA; Seattle, WA; Bellevue, WA; Santa Clara, CA; Sunnyvale, CA.
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.
Key job responsibilities We are particularly interested in candidates with expertise in: Theorem Proving, Boolean Satisfiability Solvers, Bounded Model Checking, Deductive Verification, Programming/Scripting Languages, Abstract Interpretation, Automated Reasoning, Static/Program Analysis, Program Synthesis BASIC QUALIFICATIONS
- Are enrolled in a PhD
- Are 18 years of age or older
- Work 40 hours/week minimum and commit to 12 week internship maximum
- Can relocate to where the internship is based
- Experience programming or scripting language like Python, Java, C or C++
- Experience with one or more of the following: Theorem Proving, Boolean Satisfiability Solvers, Bounded Model Checking, Deductive Verification, Programming/Scripting Languages, Abstract Interpretation, Automated Reasoning, Static/Program Analysis, Program Synthesis
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Dalhousie University Halifax, Nova Scotia
The Faculty of Computer Science at Dalhousie University invites applications for a NSERC Tier 1 Canada Research Chair (CRC) in Ocean Data Analytics. This position is designated to candidates who self-identify as a woman or member of another gender equity seeking group. The Tier 1 CRC in Ocean Data Analytics will be a tenure-track or tenured position at the rank of Associate or Full Professor (commensurate with experience) with an anticipated start date of July 1, 2025. The ideal candidate will lead groundbreaking research in Ocean Data Analytics, leveraging their fundamental expertise in artificial intelligence to address global challenges through the innovative use of ocean data. However, candidates with expertise in AI and interest in broader scopes of ocean data (e.g., fisheries, coastal-community impacts, or AI and climate technology) are also highly encouraged to apply. Most importantly, the research focus of the new CRC must be centered on two of Dalhousie’s Strategic Research Clusters: AI and Digital Innovation and Sustainable Ocean.
The successful candidate will hold a PhD in computer science or a related field, have a demonstrated capacity to lead an AI research program, and supervise graduate students in computer science. They will propose an innovative and original research program in Ocean Data Analytics, with potential applications to ocean industries and economic development, such as offshore wind, tidal energy, aquaculture, shipping, transportation, and tourism. The Chair is expected to develop a pioneering research agenda in collaboration with the Transforming Climate Action program, DeepSense as well as with industry and government initiatives. Specifically, the successful CRC will build and sustain collaborative partnerships with post-secondary institutions, provincial and federal governments, and key community partners in the oceans sector. The ideal candidate must have a proven ability to secure significant research funding and disseminate findings in impactful ways suitable to the discipline. They will engage in research leadership and promotion of interdisciplinary scholarship to create new opportunities and drive strategic directions at the intersection of artificial intelligence and ocean data analytics. Additionally, the successful candidate will contribute to complementary research areas within the Faculty and University while teaching at a reduced course load.
Applications should be made by submission of a cover letter, a detailed curriculum vitae, a three-page summary of the candidate’s research program, a one-page statement of teaching interests and philosophy, and the names and contact details of three referees. All applications are to be made through the following link: https://dal.peopleadmin.ca/postings/17974.
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About the role: We're currently looking for research scientists with specialized skills in Autonomous Driving Behavior, including, but not limited to, prediction and planning, going beyond imitation learning, and addressing closed-loop discrepancy issues. You will play a vital role in developing ML models that accurately predict the behavior of surrounding agents and plan and select optimal trajectories for our AVs. In this pivotal role, you'll be instrumental in designing and refining the ML algorithms that enable our trucks to safely navigate and operate in complex, dynamic environments. You will collaborate with a team of experts in AI, robotics, and software engineering to push the boundaries of what's possible in autonomous trucking. This role is based in our Mountain View, CA office.
What you'll do: Develop novel algorithms in agent behavior prediction and AV planning in interactive scenes Conduct research on combined prediction and planning models Work on Reinforcement Learning and other approaches to Planning beyond Imitation Learning Develop robust prediction and planning metrics for assessing the behavior systems in closed loop Push forward the cutting-edge AI closed-loop methods for use in the Autonomy Stack for both Planning and Selection Test ML models in simulation to ensure robust performance and generalization Analyze model performance and identify areas for improvement, iterating on design and implementation to enhance quality and reliability Participate in the AI Research team activities targeting internal education and external scientific image Work closely with the Production teams to push your idea into the deployment Propose new ideas and build on top of state-of-the-art knowledge
What we're looking for: You have a Ph.D. in one or more of the following areas: Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related field You have at least 1-3 years of hands-on experience in one or more of the following areas: Autonomous Driving (preferable), Robotics, or Deep Learning in general You have at least 1-3 years of research experience in one or more of the following areas: Reinforcement Learning (preferable), Behavior Prediction and/or Planning, Statistics, Probability theory Deep knowledge of Autonomous Driving Behavior including Reinforcement Learning modeling: different forms of guidance, sampling optimization, probability estimation Imitation vs Reinforcement Learning specifics Planning vs Selection Prediction vs Planning Open vs Closed loop Closed-loop training Hierarchical Planning Transformer Decoding Experience with simulation environments for autonomous vehicles, such as CARLA, Waymax, or similar platforms Strong foundation in data structures, algorithm design, and complexity analysis Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like TensorFlow/PyTorch Demonstrated ability to publish research findings in any of the top-tier technical journals and conferences (ICRA, CoRL, IROS, ICLR, ICML, NeurIPS, AAAI, IJCAI, CVPR, ICCV, ECCV, etc.) You are passionate about Autonomous Driving!
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Multiple Locations Globally
Description
Qualcomm is proud to be attending NeurIPS 2024 in Vancouver, Canada! Qualcomm is the on-device AI leader, conducting novel foundational and applied AI research, to enable intelligent computing everywhere.
We would love to know more about you, encourage you to meet us, and share upcoming hiring opportunities with the Qualcomm team. We're inviting all those who have a passion for AI and are interested in opportunities in Computer Vision, Pattern Recognition, Deep Learning, Generative AI, and Research and Development to please follow the steps below.
- Follow the URL to our NeurIPS Events Page.
- Click on the blue link to REGISTER. (This will tag your profile as someone we met at NeurIPS.)
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After REGISTERING apply to any of the below positions which can be found on our NeurIPS Events Page.
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3057992 Senior Machine Learning Researcher - Qualcomm - Amsterdam
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3057993 Principal Machine Learning Researcher - Qualcomm - Amsterdam
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3058111 Senior Machine Learning Researcher – Generative AI - Qualcomm - Amsterdam
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3061058 Staff Machine Learning Engineer
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3062221 Senior AI Cloud/Pipeline Engineer
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3063005 Cloud Services Engineer
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3063641 Senior AI Model Efficiency Open-Source Developer
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3065029 Senior System Engineer, Deep Learning/GenAI
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3065502 Program Manager, AI Research
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3066354 Machine Learning Engineer up to Sr. (Hsinchu/Taipei)
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3066353 Machine Learning Engineer, up to Sr. -Advanced Research (Hsinchu/Taipei)
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3066393 Computer Vision Systems Engineer, up to Staff
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3066985 Machine Learning for Video Compression - Principal Scientist
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3066980 Video Research Engineer
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3066984 Video Research Engineer - Immersive Video
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INTERNSHIP OPPORTUNITY
Data Science Intern(s) will work closely with members of the Data Science team, Investment Analysts, and Data Engineers to analyze, extend, and build on Viking’s significant repository of alternative data assets and generate actionable investment insights.
We seek an analytical and creative problem solver and provide them with the resources and tools to apply their Data Science training and experience to our most pressing and interesting research questions. The intern will work independently and collaborate with other intellectually curious quantitative professionals. We are open to different durations, start dates, and full-time vs. part time options for the ideal candidate. To learn more, please join our webinar on October 29 at 6:00pm EST by registering here: https://vikingglobal.zoom.us/webinar/register/WN_uwLJeTswQmieRypYwDe78A.
RESPONSIBILITIES
Activities could include but are not limited to:
• Develop and deliver predictive analytics on companies, sectors, and macroeconomic trends
• Deliver investment insights to the investment team from analysis using alternative data
• Develop methodologies to identify and evaluate investment opportunities in private companies
• Identify and evaluate new data sources
• Streamline the data life cycle, operating model, and process
• Test and evaluate new technologies to enhance our big data platform
• Create centralized and automated analyses and processes
• Contribute to Viking’s overall research effort by sharing information and insights across the firm
QUALIFICATIONS
The ideal candidate will possess the following traits:
• A strong performer currently enrolled in a Master’s degree or in a PhD program (3rd year and above) in Data Science, Economics, Finance, Statistics, or related quantitative fields
• Strong communication skills, with the ability to convey complex ideas to a non-technical audience
• Independence of thought and ability to carry out a research project with partial supervision
• Proficiency in Python and statistical libraries, working knowledge of SQL, BI software (e.g., Tableau), and cloud technologies
• Sound judgment, ability to take a step back from the analysis and look at the big picture
• Passion for research, proactive and self-motivated
APPLICATION:
• Please submit your resume / application through the Viking career site.
• Please indicate your school’s name on the application page.
• In addition to your resume, a supplement to the application is required. In 1-2 pages, describe a quantitative research project that you recently completed. Please include the following details and attach this supplement and your resume as one file when submitting:
o Research question you were trying to answer
o Data you used
o Your approach, including details on the statistical methodologies
o Your findings
o The computational environment (e.g., language, main libraries, etc.)
• Application deadline is November 11, 2024 11:59PM EST
• Our interviews will take place virtually in December.
The base salary range for this position in New York City is 175,000to250,000. In addition to base salary, Viking employees may be eligible for other forms of compensation and benefits, such as a discretionary bonus,100% coverage of medical and dental premiums, and paid lunches. Actual compensation for successful candidates will be individually determined based on multiple factors including, but not limited to, a candidate’s skill set, experience, education, and other qualifications. For more information on our benefits, please visit www.vikingglobal.com/life-at-viking/
Viking is an equal opportunity employer. Questions about your candidacy and requests for reasonable accommodation in the recruitment process should be directed to campusrecruiting@vikingglobal.com.
CONTACT:
Viking Campus Recruiting Team campusrecruiting@vikingglobal.com
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Location: New York, NY
FRF positions are initially two-year appointments, renewable for a third year contingent on performance. Fellows will be based, and have a principal office or workspace, at the Simons Foundation’s offices in New York City. Fellows may also be eligible for subsidized housing within walking distance of the Flatiron Institute. The start date is between July 2025 and October 2025.
Flatiron Research Fellows are mentored by one or more research scientists. They are also encouraged to carry out an independent research program, to collaborate across the various centers at the institute, to participate in the institute’s vibrant activities such as workshops and seminars, and to mentor students through our summer internship program. They are expected to disseminate their results through scientific publication, conferences, and/or software distribution. Fellows receive a generous travel and research budget, and have access to the institute’s powerful scientific computing resources.
Application deadline: December 15, 2024
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New York, NY
We are looking for an engineer with experience in low-level systems programming and optimization to join our growing ML team.
Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction.
Your part here is optimizing the performance of our models – both training and inference. We care about efficient large-scale training, low-latency inference in real-time systems, and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking, and host- and GPU-level considerations. Zooming in, we also want to ensure our platform makes sense even at the lowest level – is all that throughput actually goodput? Does loading that vector from the L2 cache really take that long?
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in.
There’s no fixed set of skills, but here are some of the things we’re looking for:
- An understanding of modern ML techniques and toolsets
- The experience and systems knowledge required to debug a training run’s performance end to end
- Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores, and the memory hierarchy
- Debugging and optimization experience using tools like CUDA GDB, NSight Systems, NSight Compute
- Library knowledge of Triton, CUTLASS, CUB, Thrust, cuDNN, and cuBLAS
- Intuition about the latency and throughput characteristics of CUDA graph launch, tensor core arithmetic, warp-level synchronization, and asynchronous memory loads
- Background in Infiniband, RoCE, GPUDirect, PXN, rail optimization, and NVLink, and how to use these networking technologies to link up GPU clusters
- An understanding of the collective algorithms supporting distributed GPU training in NCCL or MPI
- An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools
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Opportunities based in Australia and India
Do work that matters
Our Technology team has a unique role to enable the Group’s purpose, priority and ambition. To do this, our Technology Strategy is the vehicle which will enable this, detailing out what we're doing, when we're doing it and how we're measuring it.
We work hard to ensure that best practice, whether inside CommBank or outside in the broader technology ecosystem, is discovered, sheltered, nurtured, and spread to wherever else it can drive the most benefit for the Group and our customers.
See yourself in our team
CBA’s Distinguished Engineers will collectively influence strategic planning processes at the Group and domain level and provide technical and thought leadership to evolve our tech strategy, guide CBA in shaping our technology strategy and its execution. They will shape the development of the Engineering Practice, the horizontal construct that anchors all engineering teams and engineers across CBA.
Equally as important, the Distinguished Engineers will nurture our community of talented engineers. They will develop and mentor the next up-and-coming engineers and act as talent magnets in the industry. The creation of the Distinguished Engineer role will help CBA become the destination of choice for future engineers and STEM students and help to re-affirm CBA’s tech leadership in the industry.
Our Distinguished Engineers will adopt an enterprise mindset, working across the group to empower the engineering community by advocating for better tools, increased velocity, making sure engineers can do what they do best: engineer (commit) code into production faster, more securely and for the benefit of our customers. They will represent us at leading tech conferences and forums, influencing the tech thinking in Australia and globally.
We’re interested in hearing from experienced senior leaders with:
- Engineering expertise and technical leadership on strategic programs of high complexity and impact at Group and Domain level.
- Leading modernisation of technology functions, planning and leading implementation efforts for major redesign, refactoring, and optimization efforts.
- Participating in and influencing the strategic planning processes, providing advice and mentorship to ELT and Board
- Being visible and recognized in industry by presenting at various forums and showing industry level thought leadership, representing your organisation externally in media, event and education forums
- Driving continued professional, career and technical growth both directly as a teacher and mentor and establishment of robust development practices and culture. Provide context and clarity with regard to “what good looks like”
- Maintaining deep technical skills, including hands on software engineering and operations
Our leadership philosophy
At CommBank, leadership is a privilege, and at its core is a real desire to make a difference in the lives of our people and customers. Leadership is not tied to a title, it is a collection of beliefs and behaviours that energises others to achieve collective and sustainable outcomes.
Our leaders put customer outcomes first, are always learning and pursue our purpose with Care, Courage and Commitment. Please apply if you are keen to explore this leadership opportunity further.
*Apply by email to: Graham.eaton@cba.com.au" For more info you can also reach out to the Commonwealth Bank of Australia team at NeurIPS
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San Francisco, CA or New York City
About Scale
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.
About This Role
This role will lead the development of trust & safety models to detect fraud & violations on our platform at large scale. The ideal candidate will have experience in industry working on trust & safety to detect misuse via account and behavioral signals. Successful candidates will be impact oriented, have strong foundations in machine learning, and experience in deploying ML services to production.. This position requires not only expertise in classical machine learning but familiarity with neural networks and large language models, along with strong intuitions in regards to testing detection systems in the presence of extreme class imbalance. You will contribute to the future of AI by ensuring we deliver high quality data to leading foundation model builders by ensuring that the contributors on our platform are trustworthy and high quality.
Ideally you’d have: (-) Practical experience deploying machine learning models to production in a microservices cloud environment. (-) Familiarity with LLMs and proficiency in frameworks like scikit-learn, Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes. (-) At least three years of experience addressing sophisticated ML problems, either in a research setting or product development. (-) Strong written and verbal communication skills and the ability to operate cross-functionally. (-) Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
Nice to have: (-) Hands-on production experience developing models for detecting trust & safety violations. (-) A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.) (-)Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
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Who are we? Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.
Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
Join us on our mission and shape the future!
Why this role?
Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work.
Please Note: We have offices in Toronto, London, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role.
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New York, NY
We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform.
Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Our ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use.
We’ll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches — whether it’s neural networks, random forests, gradient-boosted trees, or sophisticated ensemble methods — to aid decision-making so we apply the right tool for the problem at hand. Your work will also focus on enhancing research workflows to tighten our feedback cycles. Successful ML engineers will be able to understand the mechanics behind various modeling techniques, while also being able to break down the mathematics behind them.
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. While there isn’t a fixed list of qualifications we’re looking for, if you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in.
We're looking for someone with:
- Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
- A strong mathematical background; Good candidates will be excited about things like optimization theory, regularization techniques, linear algebra, and the like
- A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
- A proven ability to create and maintain an organized research codebase that produces robust, reproducible results while maintaining ease of use
- Expertise wrangling an ML framework – we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow, or others
- An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools
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New York, NY
About the Program Our goal is to give you a real sense of what it’s like to work at Jane Street full time as an ML researcher. Over the course of your internship, you will explore ways to approach and solve cutting-edge machine learning problems through fun and challenging classes, interactive sessions, and group discussions — and then you will have the chance to put those lessons to practical use.
As a Machine Learning Research intern, you are paired with full-time employees who act as mentors, collaborating with you on real-world projects. Evolving our approach from simple linear models to sophisticated state-space models, Jane Street has consistently remained at the cutting edge of machine learning innovation. When you’re not working on your project, you will have plenty of time to use our office amenities, physical and virtual educational resources, attend guest speakers and social events, and engage with the parts of our work that excite you the most.
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you’ll fit right in.
About the Position Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction.
Researchers at Jane Street are responsible for building models, strategies, and systems that price and trade thousands of financial instruments algorithmically. This job involves processing petabytes of data, produced by adversarial markets, that evolve everyday. Signals are small, noise is high.
We’re looking for people with advanced machine learning experience in either an applied or academic context. A good candidate should have a deep understanding of a wide variety of ML techniques, and a passion for iterating with model architectures, feature transformations, and hyperparameters to generate robust inferences. We move fast, and want people with the ability to quickly absorb the context of a new problem, carefully consider tradeoffs, and recommend possible solutions.
You'll learn how Jane Street applies advanced machine learning and statistical techniques to model and predict moves in financial markets. Through a series of classes and activities, you will analyze real trading data via access to our growing GPU cluster containing thousands of A/H100s . You'll gain an understanding of the differences between textbook machine learning and its application to noisy financial data.
Note that given the IP sensitive nature of machine learning research at Jane Street, it is highly unlikely any research findings associated with the JS internship will be suitable for outside academic publication.
About You We don’t expect you to have a background in finance — we’re more interested in how you think and learn than what you currently know. You should be:
- An undergraduate, PhD student, or postdoc with practical experience working on ML problems
- Able to apply logical and mathematical thinking to all kinds of problems
- Intellectually curious — asking great questions is more important than knowing all the answers
- A strong programmer in Python
- An open-minded thinker and precise communicator who enjoys interacting with colleagues from a wide range of professional backgrounds and areas of expertise
- Eager to ask questions, admit mistakes, and learn new things
Apply
✍🏽 About Writer
Writer is the full-stack generative AI platform delivering transformative ROI for the world’s leading enterprises. Named one of the top 50 companies in AI by Forbes and one of the best places to work by Inc. Magazine, Writer empowers hundreds of customers like Accenture, Intuit, L’Oreal, Mars, Salesforce, and Vanguard to transform the way they work.
Writer’s fully integrated solution makes it easy to deploy secure and reliable AI applications and agents that solve mission-critical business challenges. Our suite of development tools is powered by Palmyra – Writer’s state-of-the-art family of LLMs — alongside our industry-leading graph-based RAG and customizable AI guardrails.
Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team of over 250 employees thinks big and moves fast, and we’re looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work.
📐 About this role:
We need an experienced leader for our AI research team. You'll lead research on advanced AI, focusing on large language models and reasoning agents. You'll also shape research strategy and build industry-leading language models. This role reports to the CTO.
If you're passionate about using AI to transform businesses, we want to hear from you.
🦸🏻♀️ Your responsibilities:
- Spearhead cutting-edge research: Oversee and contribute to groundbreaking projects by developing, training, and applying advanced language models ethically.
- Stay ahead of the curve: Keep up with AI advancements. Make sure your team uses the latest research. Stay competitive.
- Shape our research strategy: Create and carry out a research plan that matches Writer's long-term vision and short-term goals.
- Lead and inspire: Guide a team of applied researchers, fostering innovation and excellence.
- Bridge research and product: Collaborate with cross-functional teams to turn research into metrics and features.
- Elevate our profile: Drive high-impact research and represent Writer at top conferences and industry events.
- Grow and develop talent: Mentor, develop, and grow the research team. Give guidance and support so team members can reach their goals.
⭐️ Is this you?
- Advanced LLM applied research: Experience fine-tuning agentic models to improve their performance and utility.
- Expert-level programming: Proficiency in Python and/or C++.
- Proven AI research leadership: 6-10 years of pioneering AI research, driving innovation, and leading high-impact projects.
- Deep expertise in AI model development: Experienced in AI model research, development, and training. Proficient in model frameworks like PyTorch and TensorFlow.
- Strong publication record: Published research in top AI conferences and journals.
- Excellent interpersonal and communication skills: Proven ability to collaborate effectively with remote and cross-functional teams.
✨ Preferred skills and experience:
- Education: A Ph.D. or MS in Computer Science, AI, or a related field is highly preferred.
- People management experience: 1-3 years of people management experience.
- Experience with scalable applications: Experience building scalable applications with LLMs, using frameworks such as LangChain, LlamaIndex, Hugging Face, etc.
- Depth of knowledge with RAG implementation: Expertise in RAG (Retrieval-Augmented Generation) implementation and improvements.
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