NeurIPS 2025 Career Opportunities
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 2025.
Search Opportunities
Amsterdam
If you enjoy mathematical challenges and writing computer programs, you could be instrumental in the success of Optiver’s dynamic trading floor as our next Graduate Quantitative Researcher. With your statistics knowledge and top-tier analytical abilities, you’ll create the insights that drive our trading strategies. Get ready to collaborate with world-class Traders and Software Engineers from more than 50 countries to improve financial markets across the globe. This is your chance to get involved and see how valuable research and data are to the future of electronic trading.
WHAT YOU’LL DO: Quantitative Research acts as the foundation upon which Optiver’s trading activities are built. Our research teams – experts in a variety of STEM subjects – utilise a scientific approach to research and design our world-class trading algorithms. This means applying and developing state-of-the-art stochastic models to price options and predict market volatility, as well as utilising Monte Carlo methods. It also means developing statistical arbitrage strategies by working with petabytes of low latency, high-frequency market data sets, an extensive high-powered computing back-testing framework and much more. Optiver Researchers believe in academic discourse, and therefore invite their teammates and Traders to challenge each hypothesis. Constant testing, analysis, refinement and innovation ensures our quantitative models remain at the cutting-edge of constantly evolving capital markets – you will play a key role in keeping us there.
WHO YOU ARE: We’re looking for aspiring Quantitative Researchers who are versatile and creative in innovating and suggesting new solutions. In return, we’ll give you the freedom to pursue your ideas and implement them right into our production systems. In terms of skills and qualifications, we’re looking for: • An academic degree in Engineering, Physics, Maths, Econometrics, Computer science or equivalent, with outstanding academic achievements • Programming experience in any language (preferably Python, but C, C++, Basic, JAVA, etc. are also a plus) • Ability to apply concepts of probability, calculus and linear algebra • Competitive attitude and eagerness to constantly improve • Ability to learn quickly • Excellent verbal and written English language skills
WHAT YOU’LL GET: You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talent colleagues, working collaboratively to tackle the toughest problems in the financial markets. In addition, you’ll receive: • A performance-based bonus structure, enabling all of our employees to benefit from our global profit pool • The opportunity to work alongside best-in-class professionals from over 50 countries • 25 paid vacation days in your first year, increasing to 30 from your second year onwards • Training opportunities, discounts on health insurance, and fully paid first-class commuting expenses • Extensive office perks, including breakfast, lunch and dinner, world-class barista, in-house physio and chair massages, organised sports and leisure activities, and Friday afternoon drinks • Training and continuous learning opportunities, including access to conferences and tech events • Competitive relocation packages and visa sponsorship where necessary for expats
HOW TO APPLY: Are you interested in furthering your career on one of the most dynamic and exciting trading floors in Europe? Apply directly via the form below for the position of Graduate Quantitative Researcher. Please provide us with a CV in English. Unfortunately we cannot accept applications via email for data protection reasons.
Remote - Americas
Applied Machine Learning Engineer - Search
Every day, millions of people search for products across Shopify's ecosystem. That's not just queries—that's dreams, businesses, and livelihoods riding on whether someone finds the perfect vintage jacket or the exact drill bit they need. As a Machine Learning Engineer specializing in Search Recommendations, you'll be the one making that magic happen. With a search index unifying over a billion products, you're tackling one of the hardest search problems at unprecedented scale. We're building cutting-edge product search from the ground up using the latest LLM advances and vector matching technologies to create search experiences that truly understand what people are looking for.
Key Responsibilities:
- Design and implement AI-powered features to enhance search recommendations and personalization
- Collaborate with data scientists and engineers to productionize data products through rigorous experimentation and metrics analysis
- Build and maintain robust, scalable data pipelines for search and recommendation systems
- Develop comprehensive tools for evaluation and relevance engineering, following high-quality software engineering practices
- Mentor engineers and data scientists while fostering a culture of innovation and technical excellence
Qualifications:
- Expertise in relevance engineering and recommendation systems, with hands-on experience in Elasticsearch, Solr, or vector databases
- Strong proficiency in Python with solid object-oriented programming skills
- Proven ability to write optimized, low-latency code for high-performance systems
- Experience deploying machine learning, NLP, or generative AI products at scale (strong plus)
- Familiarity with statistical methods and exposure to Ruby, Rails, or Rust (advantageous)
- Track record of shipping ML solutions that real users depend on
This role may require on-call work
Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.
At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.
Palo Alto
Mission: Design and build the real-time data infrastructure that powers GroqCloud’s global revenue engine, processing hundreds of billions of events each day, sustaining millions of writes per second, and enabling a multi-billion-dollar business to operate in real time. Drive the intelligence layer that fuels global billing, analytics, and real-time business operations at worldwide scale.
Responsibilities & opportunities in this role: Architect high-performance data pipelines to ingest, process, and transform millions of structured and semi-structured events daily. Build distributed, fault-tolerant frameworks for streaming data from diverse sources. Create data services and APIs that make usage and billing data easily accessible across the platform. Develop lightweight tools and dashboards to monitor and visualize data ingestion, throughput, and system health.
Ideal candidates have/are: Strong background in real-time data processing, distributed systems, and analytics infrastructure. Hands-on experience with streaming technologies such as Kafka, Flink, Spark Streaming, or Redpanda and real-time analytics databases such as Clickhouse, Druid, or Pinot. Deep understanding of serialization, buffering, and data flow optimization in high-throughput systems.
Bonus points: Experience deploying and managing workloads on Kubernetes. A passion for systems performance, profiling, and low-latency optimization. Familiarity with gRPC and RESTful API design.
Attributes of a Groqster: Humility – Egos are checked at the door Collaborative & Team Savvy – We make up the smartest person in the room, together Growth & Giver Mindset – Learn it all versus know it all, we share knowledge generously Curious & Innovative – Take a creative approach to projects, problems, and design Passion, Grit, & Boldness – No-limit thinking, fueling informed risk taking
Location USA, WA, Seattle USA, NY, New York USA, CA, Palo Alto
Description The Sponsored Products and Brands (SPB) team at Amazon Ads is reimagining the advertising landscape through generative AI, revolutionizing how millions of customers discover products and engage with brands on Amazon and beyond. We are at the forefront of redefining advertising experiences—bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle, from ad creation and optimization to performance measurement and customer insights.
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance advertiser needs, enhance the shopping experience, and strengthen the Amazon marketplace. If you are energized by solving complex challenges and pushing the boundaries of what’s possible with AI, join us in shaping the future of advertising.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.
Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Deep Learning Computer Architecture teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.
Throughout the 12-week minimum full-time internship, students will work on projects that have a measurable impact on our business. We’re looking for students pursuing Bachelor's, Master's, or PhD degree within a relevant or related field.
What we need to see: Must be actively enrolled in a university pursuing a Bachelor's, Master's, or PhD degree in Electrical Engineering, Computer Engineering, or a related field, for the entire duration of the internship.
Course or internship experience related to the following areas could be required:
Computer Architecture experience in one or more of these focus areas: GPU Architecture, CPU Architecture, Deep Learning, GPU Computing, Parallel Programming, or High-Performance Computing Systems
GPU Computing (CUDA, OpenCL, OpenACC), GPU Memory Systems, Deep Learning Frameworks (PyTorch, TensorFlow, Keras, Caffe), HPC (MPI, OpenMP)
Modelling/Performance Analysis, Parallel Processing, Neural Network Architectures, GPU Acceleration, Deep Learning Neural Networks, Compiler Programming
Performance Modeling, Profiling, Optimizing, and/or Analysis
Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies:
C, C++, Python, Perl, GPU Computing (CUDA, OpenCL, OpenACC), Deep Learning Frameworks (PyTorch, TensorFlow, Caffe), HPC (MPI, OpenMP)
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.
You will also be eligible for Intern benefits.
Applications are accepted on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Shanghai
Our Research Summer Internship program will give you real insights into how data and research is used to improve global financial markets. Expand your knowledge of the financial markets and solve challenging problems that could impact the way we trade. Plus, if you’ve excelled over the summer and shown us your potential, you could receive an offer to join us as a graduate quantitative researcher. With Optiver’s internship program, your work improving the market starts today.
Who we are: Optiver is a global market maker founded in Amsterdam, with offices in London, Chicago, Austin, New York, Sydney, Shanghai, Hong Kong, Singapore, Taipei and Mumbai. Established in 1986, today we are a leading liquidity provider, with close to 2,000 employees in offices around the world, united in our commitment to improve the market through competitive pricing, execution and risk management. By providing liquidity on multiple exchanges across the world in various financial instruments we participate in the safeguarding of healthy and efficient markets. We provide liquidity to financial markets using our own capital, at our own risk, trading a wide range of products: listed derivatives, cash equities, ETFs, bonds and foreign currencies.
What you’ll do: As a Quantitative Research Intern, you’ll work with our researchers and traders on real-life research projects, that directly impact the way we trade. Our quantitative researchers are responsible for the accuracy of our core pricing models. They work closely with our traders to analyse and improve all facets of our trading strategies. As part of the internship, you’ll get to: • Perform extensive analysis in order to implement new algorithms that support and improve our existing models. • Develop risk management and portfolio optimisation tools to improve our execution algorithm. • Work with petabytes of low latency, high-frequency market data sets. • Collaborate with our developers to test and drive changes to our trading system, that will improve our ability to make successful trades. • Keep up to date on the latest development of new models and technologies • No previous experience in trading or financial markets? You bring the passion and we’ll have the training to support you along the way
Who you are: • PhD student, who will graduate during 2028. • Major in a highly quantitative field. • Strong knowledge of probability and statistics, experience in machine learning and time-series analysis is a big plus. • Programming experience in any language (C, C++, Python, JAVA, etc.), ideally with a preference towards Python. • Ability to carry a project on your own in a structured way within a short timeframe. • Experience in working with large datasets. • Both a self-motivated contributor and a team player, with an entrepreneurial attitude and hunger for success. • Interest in the trading/quantitative finance industry.
What you’ll get: • The chance to work alongside diverse and intelligent peers in a rewarding environment. • Competitive remuneration, including an attractive bonus structure and additional leave entitlements. • Training, mentorship and personal development opportunities. • Daily breakfast, lunch and snacks. • Gym membership, sports and leisure activities, plus weekly in-house chair massages. • Regular social events, clubs and Friday afternoon drinks.
How to apply: If you’re interested in taking your career to the next level and work on one of the most exciting trading floors in China mainland, apply now via the form below. While we love how bilingual our teams are, be sure to submit the below application materials in English: • Resume • Academic transcripts, including Bachelors and Masters and PhD if any
For any other inquiries, please email chinacareers@optiver.com.au.
Pinely is a privately owned algorithmic trading firm specializing in high-frequency and mid-frequency trading. We’re based in Amsterdam, Cyprus, and Singapore, and we’re experiencing rapid growth. Pinely is a high-frequency algorithmic trading firm based in Amsterdam. We develop robust and adaptive strategies across diverse markets and actively support the Olympiad movement; many team members are award-winning mathematicians, researchers, and engineers.
Researchers work in a fast-paced HFT environment where ideas quickly reach production. They are supported by a strong infrastructure team enabling large-scale experiments and reliable deployment. Our flat structure encourages autonomy, creativity, and direct impact. We value an informal, idea-driven culture.
We are opening a position for a Junior Deep Learning Researcher in our Amsterdam office.
Responsibilities:
- Conduct research in AI, machine learning, and related quantitative fields
- Develop and experiment with modern deep learning architectures
- Analyze large, unstructured, noisy datasets
- Collaborate with developers and researchers on optimizing trading strategies
- Explore new methods and technologies to improve research outcomes
Requirements:
- Publications in ICML, NeurIPS, ICLR, CVPR, ICCV
- Degree in mathematics, physics, computer science, or another quantitative field (or expected within a year)
- Knowledge of ML, probability theory, and statistics
- Strong Python skills
- Some C++ experience
- Practical experience with modern DL architectures
- Background in working with large noisy datasets
What we offer:
- High base salary with substantial biannual bonuses
- Relocation package to Amsterdam with flexible terms
- Flexible workflow and schedule
- Team of top mathematics and programming competition winners
- Cutting-edge hardware, strong engineering support, and fast idea implementation
- Internal training, comprehensive health insurance, sports reimbursement, and biannual corporate events
The Department of Materials Science and Engineering (DMSE) together with the Schwarzman College of Computing (SCC) at Massachusetts Institute of Technology (MIT) in Cambridge, MA, seeks candidates at the level of tenure-track Assistant Professor to begin July 1, 2026 or on a mutually agreed date thereafter.
Materials engineering has always benefitted from theoretical and computational approaches to unveil relationships between structure, properties, processing, and performance. Recent advances in computing, including but not limited to artificial intelligence, are poised to dramatically advance the understanding and design of complex matter. DMSE and SCC jointly seek candidates with experience and interest in combining fundamental scientific principles with algorithmic innovations to empower discovery, understanding, and synthesis of materials with applications across critical societal domains --- healthcare, manufacturing, energy, sustainability, climate, and next-generation computing. This search encompasses all materials classes and scales, and is open to candidates with industry and start-up experience. Candidates are expected to develop research programs that target innovation in computational approaches well-suited to materials science and engineering research.
The successful candidate will have a shared appointment in both the Department of Materials Science and Engineering and SCC in either the Department of Electrical Engineering and Computer Science (EECS) or the Institute for Data, Systems, and Society (IDSS), depending on best fit.
Faculty duties include teaching at the undergraduate and graduate levels, advising students, conducting original scholarly research, and developing course materials at the graduate and undergraduate levels. Candidates are expected to teach in both the Department of Materials Science and Engineering and in the educational programs of SCC. The normal teaching load is two subjects per year.
Candidates should hold a Ph.D. in Materials Science and Engineering, Computer Science, Physics, Chemical Engineering, Chemistry, Applied Mathematics, or a related field. A PhD is required by the start of employment. The pay range for a 9-month academic appointment at the entry-level Assistant Professor rank (excluding summer salary): $140,000 - $150,000. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the individual's work experience and education/training, internal peer equity, and applicable legal requirements. These factors impact where an individual's pay falls within a range. Employment is contingent upon the completion of a satisfactory background check, including verifying any finding of misconduct (or pending investigation) from prior employers.
Applications should include: (a) curriculum vitae, (b) research statement, (c) a teaching and mentoring plan. Each candidate should also include the names and contact information of 3 reference letter writers, who should upload their letters of recommendation by November 30, 2025.
Please submit online applications to https://faculty-searches.mit.edu/dmse_scc/register.tcl. To receive full consideration, completed applications must be submitted by November 30, 2025.
MIT is an equal opportunity employer. We value diversity and strongly encourage applications from individuals from all identities and backgrounds. All qualified applicants will receive equitable consideration for employment based on their experience and qualifications and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, pregnancy, religion, disability, age, genetic information, veteran status, or national or ethnic origin. See MIT's full policy on nondiscrimination. Know your rights.
Pittsburgh
We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and recognize multimodal human behavior in real world settings (e.g., Affective Computing, AI for Healthcare: pain measurement, monitoring mental health disorders). The successful candidate will have primary responsibility for all facets of the project, including papers writing and students mentoring. Preference will be given to candidates with a proven track record, demonstrating relevant skills and extensive experience in multimodal machine learning and human behavior analysis (e.g., facial and gesture analysis and acoustic signal processing). The candidate should be enthusiastic about collaborating with partners from multiple disciplines and institutions.
Preference for on-site candidates in San Mateo, but remote possible.
BigHat is hiring a Principal ML Scientist. We've got an awesome high-throughput wetlab that pumps proprietary data into custom ETL and ML Ops infra to power our weekly design-build-train loop. Come solve hard-enough-to-be-fun problems in protein engineering in service of helping patients!