NeurIPS 2025 Career Opportunities

The Chan Zuckerberg Institute for Advanced Biological Imaging (CZ Imaging Institute) is building the next generation of imaging technologies to transform our understanding of biology in health and disease. Over the next decade, we aim to create breakthrough systems — spanning hardware, software, probes, and computational tools — that will empower scientists worldwide.

As part of the Chan Zuckerberg Initiative’s Imaging Program, the CZ Imaging Institute (https://czii.org/) combines engineering, computation, and biology to tackle grand challenges in biological imaging. Our work is shared broadly with the global scientific community through open science, direct collaborations, and partnerships.

The CZ Imaging Institute will create breakthrough technologies — hardware, software, biological probes, data, and platforms — that will be made available to the scientific community and adopted worldwide through a combination of direct access to the institute, open sharing of advances, and commercial partnerships. Researchers will collaboratively develop breakthrough biological imaging systems centered around grand challenges that push the boundaries of what we can see and measure.

We are seeking a creative and motivated Data Scientist to develop and apply cutting-edge computational methods for complex imaging problems. This role is ideal for candidates with expertise in applied mathematics, computational science, or physics, combined with modern machine learning approaches. You will design algorithms, build scalable tools, and collaborate across disciplines to advance scientific discovery.

This position is on-site in Redwood City, CA.

What You'll Do - Develop and apply algorithms for solving inverse problems in imaging and related computational challenges. - Use optimization, applied mathematics, and physics-inspired modeling to extract insights from high-dimensional data. - Incorporate modern machine learning and deep learning techniques to improve reconstruction, denoising, and feature detection. - Build robust, scalable pipelines for large-scale biological datasets. - Collaborate with biologists, microscopists, and engineers to design solutions aligned with scientific goals. - Contribute to technical documentation, publications, and presentations.

What You'll Bring - M.S. or Ph.D. in Applied Mathematics, Computer Science, Physics, Engineering, or a related field. - 1 - 5 years of relevant experience. - Strong foundation in inverse problems, optimization, or computational modeling. - Experience in machine learning and deep learning (e.g., PyTorch, TensorFlow). - Proficiency in Python or C++, and familiarity with scientific computing libraries. - Strong analytical, problem-solving, and communication skills. - Experience with imaging data (e.g., cryo-EM, tomography, or related modalities). - Familiarity with convex optimization, variational methods, or numerical PDEs. - Knowledge of GPU computing and high-performance environments. - Track record of scientific publications or open-source contributions.

The Chan Zuckerberg Biohub Network (https://www.czbiohub.org/) is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The CZ Biohub Network focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies.

We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at the CZ Biohub Network facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and perspectives are at the heart of CZ Biohub Network and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

The Biohub Network is seeking an accomplished computational biologist and machine learning/AI specialist to join our interdisciplinary team. This role requires experience in research settings, a background in biology, and a proven ability to design, evaluate, and publish innovative computational methodologies that leverage machine learning, statistics, language modelling, and AI to advance biological research and discovery. Research projects to accelerate the rate of scientific discovery will be assigned by the President of the New York location, and in collaboration with research teams across the organization.

The ideal candidate will have a strong track record of accomplishments and a dedication to collaborative work within a highly interdisciplinary environment.

This role is based out of the New York location.

What You'll Do - Contribute to a dynamic, innovative, and collaborative program that aligns with the mission of CZ Biohub NY. - Develop and evaluate cutting-edge computational / AI methodologies using data generated from across all research groups and incorporating relevant available datasets for to develop predictive models. - Collaborate within an interdisciplinary research environment to develop, test, and validate models. - Engage with colleagues throughout the Biohub to uphold our values of scholarly excellence, innovation, open communication, hands-on hacking, and partnership. - Communicate progress and results with colleagues inside and outside of your team. - Publish and disseminate impactful findings through preprints (medRxiv, bioRxiv) and/or software repositories (e.g., GitHub). - Work with the CZ Biohub team to patent and license technologies resulting from your research.

What You'll Bring - PhD in Computational Biology, AI / Machine learning, Applied Statistics or a MS plus relevant job experience. - Background in relevant areas of biomedical science, demonstrating a deep understanding of cellular biology, transcription and protein signal transduction. - 2-4 years of post-doctoral and/or industry experience demonstrating the ability to implement, evaluate, and create new computational methodologies that leverage machine learning, statistics, and AI for biological research and discovery. - Experience in building and evaluating machine learning and/or neural network models on biological data, with a deep understanding of feature selection, regularization, model introspection, and interpretability. - Proficiency in using and modifying probabilistic learning or deep learning models such as RNNs, GNNs, protein sequence models, or natural language processing models. - Proven track record of individual innovation, as well as a strong ability to work collaboratively. - Outstanding interpersonal and communication skills. - Demonstrated commitment to open science and alignment with the mission and values of CZ Biohub.

Remote US or Canada

Mission: Join the team that builds and operates Groq’s real-time, distributed inference system delivering large-scale inference for LLMs and next-gen AI applications at ultra-low latency. As a Low-Level Production Engineer, your mission is to ensure reliability, fault tolerance, and operational excellence in Groq’s LPU-powered infrastructure. You’ll work deep in the stack—bridging distributed runtime systems with the hardware—to keep Groq systems fast, stable, and production-ready at scale.

Responsibilities & opportunities in this role: Production Reliability: Operate and harden Groq’s distributed runtime across thousands of LPUs, ensuring uptime and resilience under dynamic global workloads. Low-Level Debugging: Diagnose and resolve hardware-software integration issues in live environments, from datacenter level events to single component failures. Observability & Diagnostics: Build tools and infrastructure to improve real-time system monitoring, fault detection, and SLO tracking. Automation & Scale: Automate deployment workflows, failover systems, and operational playbooks to reduce overhead and accelerate reliability improvements. Performance & Optimization: Profile and tune production systems for throughput, latency, and determinism—every cycle counts. Cross-Functional Collaboration: Partner with compiler, hardware, infra, and data center teams to deliver robust, fault-tolerant production systems.

Ideal candidates have/are: Proven experience in production engineering across the stack and operating large-scale distributed systems. Deep knowledge of computer architecture, operating systems, and hardware-software interfaces. Skilled in low-level systems programming (C/C++ or Rust), with scripting fluency (Python, Bash, or Go). Comfortable debugging complex issues close to the metal—kernels, firmware, or hardware-aware code paths. Strong background in automation, CI/CD, and building reliable systems that scale. Thrive across environments—from kernel internals to distributed runtimes to data center operations. Communicate clearly, make pragmatic decisions, and take ownership of long-term outcomes.

Nice to have: Experience operating high-performance, real-time systems at scale (ML inference, HPC, or similar). Familiarity with GPUs, FPGAs, or ASICs in production environments. Prior exposure to ML frameworks (e.g., PyTorch) or compiler tooling (e.g., MLIR). Track record of delivering complex production systems in high-impact environments.

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

Toronto

Description - Bloomberg’s Engineering AI department comprises over 350 AI experts dedicated to building cutting edge, market-leading products. Leveraging advanced technologies including transformers, large language models, and dense vector databases, we are transforming search, discovery, and workflow solutions across the financial industry. As we expand our group, we are seeking highly skilled Machine Learning (ML) and Software Engineers who will contribute innovative solutions to AI-driven customer-facing products.

At Bloomberg, we foster transparency and efficiency in global financial markets. Our technology powers search and discoverability, bringing actionable insights from news, research, financial data, and analytics covering more than 35 million financial instruments. Since 2009, Bloomberg has been at the forefront of applying artificial intelligence to organize the vast volumes of structured and unstructured data that inform critical financial decisions, uncover market signals, and deliver clarity precisely when our clients need it most.

In Toronto, our Machine Learning Engineers are central to advancing Bloomberg’s efforts in financial query understanding and code generation. They bridge the gap between pioneering research and practical solutions, developing models to address complex financial queries and automate code writing. They engineer state-of-the-art code generation systems and apply LLM techniques like CoT, SFT or RLHF to drive iterative model refinement.

Join the AI Group as a Senior ML Research Engineer and you will have the opportunity to: -Collaborate with colleagues on production systems and write, test, and maintain production quality code -Design, train, experiment, and evaluate ML models, algorithms and solutions -Demonstrate technical leadership by owning cross-team projects -Stay current with the latest research in ML and incorporate new findings into our models and methodologies -Represent Bloomberg at scientific and industry conference and in open-source communities -Publish product and research findings in documentation, whitepapers or publications to leading academic venues

We are looking for Senior ML Research Engineers with the following experience: -Practical experience with solving Machine Learning problems and techniques -Ph.D. in ML, Statistics or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and 2+ years of relevant work experience -Experience with machine learning and deep learning frameworks -Proficiency in software engineering -An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving -Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders. -A track record of authoring publications in top conferences and journals is a strong plus

Location Chicago; New York

Description:

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.

Other duties as assigned or needed.

Skills You’ll Need:

• Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
• Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
• Solid development skills in Python and/or C++
• Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, and/or JAX
• Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
• Ability to thrive in a collaborative, team-oriented environment
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Reliable and predictable availability required

Bonus Points:

• Experience with HPC and distributed large model training
• Experience with GPU performance optimization (CUDA or ROCm)
• Experience with end-to-end model development
• Strong opinions on best practices in ML research, tooling, and/or infrastructure

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role is $300,000 per year.

Palo Alto, CA

Position Description: Tesla is looking for strong Machine Learning Engineers to help build foundation models for robotics to drive the future of autonomy across all current and future generations of vehicles. You will work on a lean team without boundaries and have access to one of the world’s largest training clusters. Most importantly, you will see your work repeatedly shipped to and utilized by millions of Tesla’s customers.

Responsibilities: Leverage millions of miles of driving data and interventions to build a robust and scalable end-to-end learning based self-driving system Use cutting-edge techniques from generative modeling, imitation learning, and reinforcement learning to improve the planning and reasoning capabilities of our driving models Experiment with data generation and fleet data collection approaches to enhance the diversity and quality of training data Integrate directly with vehicle firmware and ship production quality, safety-critical software to the entirety of Tesla's vehicle fleet

Requirements: Strong experience with Python, any major deep learning framework, and software engineering best practices An "under the hood" knowledge of deep learning modern architectures, optimization, model alignment, etc. Proven expertise in deploying production ML models for self-driving, robotics, or natural language processing at scale Comfort with C++ to help integrate with vehicle firmware and take projects from ideas to shipped products

Location USA, CA, Sunnyvale USA, WA, Seattle

Description Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.

As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.

We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!

We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide.

Location United States

Description At Oracle Cloud Infrastructure (OCI), we are building the future of cloud computing—designed for enterprises, engineered for performance, and optimized for AI at scale. We are a fast-paced, mission-driven team within one of the world’s largest cloud platforms. The Multimodal AI team in OCI Applied Science is working on developing cutting-edge AI solutions using Oracle's industry leading GPU-based AI clusters to disrupt industry verticals and push the state-of-the-art in Multimodal and Video GenAI research. You will work with a team of world-class scientists in exploring new frontiers of Generative AI and collaborate with cross-functional teams including software engineers and product managers to deploy these globally for real-world enterprise use-cases at the largest scale.

Responsibilities: - Contribute to the development and optimization of distributed multi-node training infrastructure - Stay Updated: Maintain a deep understanding of industry trends and advancements in video generatio, multimodal understanding, pretraining workflows and paradigms. -Model Development: Design, develop, and train state-of-the-art image and vide generation models that meet the highest quality standards. - Collaborate with cross-functional teams to support scalable and secure deployment pipelines. - Assist in diagnosing and resolving production issues, improving observability and reliability. - Write maintainable, well-tested code and contribute to documentation and design discussions

Minimum Qualifications - BS in Computer Science or related technical field. - 6+ years of experience in backend software development with cloud infrastructure. - Strong proficiency in at least one language such as Go, Java, Python, or C++. - Experience building and maintaining distributed services in a production environment. - Familiarity with Kubernetes, container orchestration, and CI/CD practices. - Solid understanding of computer science fundamentals such as algorithms, operating systems, and networking.

Preferred Qualifications - MS in Computer Science. - Experience in large-scale multi-node distributed training of LLMs and multimodal models. - Knowledge of cloud-native observability tools and scalable service design. - Interest in compiler or systems-level software design is a plus.

Why Join Us - Build mission-critical AI infrastructure with real-world impact. - Work closely with a collaborative and experienced global team. - Expand your knowledge in AI, cloud computing, and distributed systems. - Contribute to one of Oracle’s most innovative and fast-growing initiatives.

Disclaimer:

Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $96,800 to $223,400 per annum. May be eligible for bonus and equity.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle’s differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees

NVIDIA is searching for an outstanding researcher working on efficient deep learning to join the deep learning efficiency research team. We are passionate about research that pushes boundaries but also has impact in the real world. We are particularly excited about methods for post-training model optimization (pruning, quantization, NAS), efficient architecture design, adaptive/dynamic inference, resource-efficient training and finetuning, and so forth. You will work within an amazing and collaborative research team that consistently publishes at the top venues in computer vision and machine learning. Our existing expertise includes computer vision, deep learning, generative models, and so forth. Your contributions have the chance to create real impact on our products.

What you'll be doing: Research, design and implement novel methods for efficient deep learning.

Publish original research.

Collaborate with other team members and teams.

Mentor interns.

Speak at conferences and events.

Work with product groups to transfer technology.

Collaborate with external researchers.

What we need to see: Completing or recently completed a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or have equivalent research experience.

Excellent knowledge of theory and practice of computer vision methods, as well as deep learning.

Background in pruning, quantization, NAS, efficient backbones, and so on, is a plus.

Experience with large language models and large vision-language models is required.

Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA) is a plus.

Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.

Outstanding research track record.

Excellent communications skills.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

The base salary range is 160,000 USD - 258,750 USD.

You will also be eligible for equity and benefits.

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.

Cupertino, California

Horizon Robotics (HKEX: 9660) is a leading provider of Smart Driving solutions for passenger vehicles, empowered by our proprietary software and hardware technologies. Our solutions combine cutting-edge algorithms, purpose-built software and processing hardware, providing the core technologies for smart driving that enhance the safety and experience of drivers and passengers. Horizon Robotics is key enabler for the smart vehicle transformation and commercialization with our integrated solutions deployed at scale.

The Silicon Valley Applied Research Lab is a research team located in Silicon Valley, dedicated to developing advanced algorithms and models for Advanced Driver Assistance Systems (ADAS), Autonomous Driving (AD) , and other generic robotics systems.

If you are looking for a role to explore, develop and innovate machine learning algorithms for AD and robotics technologies, you are welcome to join us.

Your Daily Practice

As an applied research scientist, you will take part in:

• Devising novel deep-learning based algorithms and converting them to prototypes of autonomous driving solutions, including but not limited to training foundation models, post-training with reinforcement learning, and world models.
• Practicing end-to-end machine learning skills, including data pipelining, model construction and fine-tuning, and comprehensive performance testing.
• Following closely with academia, identifying the latest trends and extending them to real industrial development.
• Publishing research papers in top notch conferences in machine learning domain.
• Showcasing the work via presentation in internal and external talks, conferences, and workshops.

What You Must Have

• PhD / MS degree in computer vision, machine learning or a related field with multiple research publications in top conferences or journals; alternatively equivalent years of industry experience solving CV problems which do not have readily available solutions.
• Expertise in at least one of these specific areas: deep learning-based perception, prediction and planning, vision-language models, and reinforcement learning.
• Track record of driving ML research projects from start to completion, including conception, problem definition, experimentation, iteration, and publication or productization.
• Strong programming skills in Python and/or C++.
• Extensive experience with ML frameworks such as PyTorch and Jax.
• Strong verbal and written communication skills.

Bonus points! - Track record in innovative solutions to real-world problems in machine learning domain. - Experienced with closed-loop methods in solving prediction and planning problems.

This is a hybrid role with the expectation of working at least 3 days per week in our Cupertino office. The base pay range for this full-time Applied Research Scientist position is between $150,000 and $300,000/year plus equity incentive, depending on your experience, qualifications, education, skills and other related factors.

This position is also eligible for an annual performance bonus and a competitive benefits package. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, Paid Holidays, Sick Days and Personal Time Off. We also sponsor H-1B visas and green card petitions.

Horizon Robotics is committed to be an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.