NeurIPS 2025 Career Opportunities

USA or International

The Renaissance Philanthropy Engineering Hub provides on-demand development technical assistance in support of grant-funded educational technology projects. Our support allows mission-driven teams to overcome hurdles and achieve their technical and impact goals. As a Research Engineer, you will provide technical strategy and hands-on guidance to product and research teams by developing proof-of-concepts that explore new applications of generative AI and validate the viability of emerging approaches. Visit the URL above to learn more!

New York

Quantitative Analyst Ph.D. Intern (New York) – Summer 2026

The D. E. Shaw group seeks talented Ph.D. candidates with impressive records of academic and/or professional achievement to join the firm as quantitative analyst interns. Ph.D. interns explore how the analytical skills gained from their graduate programs may relate to the work done at the firm while interacting with fellow interns and employees of similar academic backgrounds in a collegial working environment. This 12-week program will take place in New York and is expected to run from June to August 2026. 

What you'll do day-to-day

You’ll spend the summer working on a research project that typically involves exploring a variety of statistical modeling techniques and writing software to analyze financial data. You’ll have a dedicated mentor in one of our quantitative research groups and are encouraged to attend our academic speaker series and track academic progress in various areas that may be of interest.

Who we're looking for

• Individuals with impressive records of academic achievement, including advanced coursework in fields such as math, statistics, physics, engineering, computer science, or other technical and quantitative programs. 
• Applicants should have notable research productivity in their respective areas of study as well as a track record of creativity in their field(s). 
• Interest or experience working in a data-driven research environment, including manipulation of data using high-level programming languages such as Python, is preferred. 
• An exceptional aptitude for abstract reasoning, problem solving, and quantitative thinking, in addition to prior probability or statistics knowledge, is a plus. 
• No previous finance experience is necessary, though candidates should have an interest in learning about quantitative finance.
• Students who apply to this internship are usually approaching their final year of full-time study.
• The position offers a monthly base salary of 25,000USD, overtime pay, a sign-on bonus of 25,000USD, travel coverage to and from the internship, and choice of furnished summer housing or a 10,000USD housing allowance. It also includes a 3,300USD stipend for self-study materials and a 4,000USD stipend for personal technology equipment. If you have any questions about the compensation, please ask one of our recruiters.

Redwood City, CA

Biohub is leading the new era of AI-powered biology to cure or prevent disease through its 501c3 medical research organization, with the support of the Chan Zuckerberg Initiative.

The Team Biohub supports the science and technology that will make it possible to help scientists cure, prevent, or manage all diseases by the end of this century. While this may seem like an audacious goal, in the last 100 years, biomedical science has made tremendous strides in understanding biological systems, advancing human health, and treating disease.

Achieving our mission will only be possible if scientists are able to better understand human biology. To that end, we have identified four grand challenges that will unlock the mysteries of the cell and how cells interact within systems — paving the way for new discoveries that will change medicine in the decades that follow:

Building an AI-based virtual cell model to predict and understand cellular behavior Developing novel imaging technologies to map, measure and model complex biological systems
Creating new tools for sensing and directly measuring inflammation within tissues in real time.tissues to better understand inflammation, a key driver of many diseases Harnessing the immune system for early detection, prevention, and treatment of disease The Opportunity At Biohub, we are generating unprecedented scientific datasets that drive biological modeling innovation:

Billions of standardized cells of single-cell transcriptomic data, with a focus on measuring genetic and environmental perturbations 10s of thousands of donor-matched DNA & RNA samples PB-scale static and dynamic imaging datasets TB-scale mass spectrometry datasets Diverse, large multi-modal biological datasets that enable biological bridges across measurement types and facilitate multi-modal model training to define how cells act. After model training, we make all data products available through public resources like CELLxGENE Discover and the CryoET Portal, used by tens of thousands of scientists monthly to advance understanding of genetic variants, disease risk, drug toxicities, and therapeutic discovery.

As a Senior Staff Data Scientist, you'll lead the creation of groundbreaking imaging datasets that decode cellular function at the molecular level, describe development, and predict responses to genetic or environmental changes. Working at the intersection of data science, biology, and AI, you'll define data needs, format standards, analysis approaches, quality metrics, and our technical strategy, creating systems to ingest, transform, and validate and deploy data products.

Success for this role means delivering high-quality, usable datasets that directly address modeling challenges and accelerate scientific progress. Join us in building the data foundation that will transform our understanding of human biology and move us along the path to curing, preventing, and managing all disease.

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

Salesforce AI Research advances AI techniques that pave the path for new AI research directions, innovative products, and applications with a positive impact on society. Our team of researchers, engineers, product managers, and designers drives AI innovation across pure research, applied research, and new product incubation—all built on our powerful AI platform. We bring companies and customers together using explainable, transparent, and accountable AI.

As part of our team, you’ll gain unique skills, work with talented people, and influence the industry standard for the fair and ethical use of artificial intelligence to help us shape the future of AI.

Check out our website to learn more about the groundbreaking work of the Salesforce AI Research Team.

Salesforce Research is looking for outstanding research interns. Ideal candidates have a strong background in one or more of the following core areas:

Natural Language Processing (NLP) Computer Vision (CV) Reinforcement Learning (RL) General Machine Learning (ML)

Our research focus includes, but is not limited to, the following cutting-edge areas:

AI Agents Large Language/Action Modeling Responsible & Trusted AI Human-AI Interaction AI for Software Developers AI for Operations / Time Series AI for Knowledge Management Mobile AI Multimodal AI Automatic Evaluation

Candidates that have published in top-tier conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, CHI) are highly preferred.

ROLE & RESPONSIBILITIES: Collaborate with a team of research scientists and engineers on a project designed to lead to a submission at a top-tier conference. Develop novel algorithms and techniques that can be applied to real-world customer challenges within the Salesforce ecosystem. Contribute to the AI community by focusing on pure research that aligns with your PhD focus area. Learn about exciting research and applications outside your expertise. Attend conferences with our researchers to showcase accepted papers (when applicable).

MINIMUM REQUIREMENTS: PhD or MS candidate in a relevant research area. Strong background in machine learning, natural language processing, computer vision, or reinforcement learning. Excellent understanding of deep learning techniques, including CNN, RNN, LSTM, GAN, attention models, and optimization methods. Experience with one or more deep learning libraries and platforms (e.g., PyTorch, TensorFlow). Strong algorithmic problem-solving skills. Programming proficiency in Python, Java, C/C++, Lua, or a similar language.

INTERNSHIP DETAILS: This internship is a minimum of 12 weeks.

New York

Flow Traders is looking for a Senior Research Engineer to join our Hong Kong office. This is a unique opportunity to join a leading proprietary trading firm with an entrepreneurial and innovative culture at the heart of its business. We value quick-witted, creative minds and challenge them to make full use of their capacities.

As a Senior Research Engineer, you will be responsible for helping to lead the development of our trading model research framework and using it to conduct research to develop models for trading in production. You'll expand the framework to become global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.

What You Will Do

• Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production
• Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals

What You Need to Succeed

• Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
• 8+ years of hands-on experience MLOps, Research Engineering, or ML Research
• A strong background in mathematics and statistics
• Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray.
• Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
• Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
• Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)

Locations: New York, Chicago, London, Amsterdam, Hong Kong, Sydney

IMC is looking for experienced quant researchers to develop high to mid frequency trading strategies and predictive models for the global markets. If you’re excited about helping to push the boundaries of what we can do with Machine Learning in trading, unlocking the significant edges we have in execution, and collaborating to become the best trading firm worldwide, there's a role for you at IMC.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

With more than 600 million users around the world and 400 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

We are seeking talented Staff Machine Learning Engineers for multiple openings across our Core Engineering organization, including teams such as Search, Notifications, and Content & User Engineering. In these roles, you will drive the development of state-of-the-art applied machine learning systems that power core Pinterest experiences.

What you’ll do:

• Design features and build large-scale machine learning models to improve user ads action prediction with low latency
• Develop new techniques for inferring user interests from online and offline activity
• Mine text, visual, and user signals to better understand user intention
• Work with product and sales teams to design and implement new ad products

What we’re looking for:

• Degree in computer science, machine learning, statistics, or related field
• 6+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
• 2+ years of experience leading projects/teams
• Strong mathematical skills with knowledge of statistical methods
• Cross-functional collaborator and strong communicator

Palo Alto, CA

Position Description: Tesla’s AI team is pushing the frontier of real-world machine learning, building models that reason, predict, and act with human-level physical intelligence. We train and deploy large-scale ML systems powering products from Autopilot to Optimus.

As part of the Model Optimization group, you will work at the intersection of machine learning and systems, designing our most advanced models to run efficiently across Tesla’s diverse compute stack, from data centers to edge AI accelerators. You will design the model architecture and engineer algorithmic optimizations that make large-scale model inference fast, reliable, and hardware-aware.

Responsibilities: Design, train, and deploy large neural networks that run efficiently on heterogeneous hardware (GPU, CPU, Tesla’s in-house AI ASIC) Develop and integrate quantization, sparsity, pruning, and distillation techniques to improve inference performance Design inference algorithms that improve inference performance in terms of quantization and latency Profile and improve latency, throughput, and memory efficiency for large ML models across edge and cloud environments Collaborate with compiler and hardware engineers to co-design architectures for efficient real-time inference Design and implement custom GPU kernels (CUDA / OpenCL) to accelerate model operations and post-processing pipelines Conduct systematic benchmarking, scaling, and validation of inference performance across Tesla platforms

Requirements: Proven experience in scaling and optimizing inference for large ML models, particularly transformers or similar architectures Familiarity with quantization-aware training, model compression, and distillation for edge and real-time inference Proficiency with Python and C++ (modern standards 14/17/20) and deep learning frameworks such as PyTorch, TensorFlow, or JAX Strong understanding of computer systems and architecture, with experience deploying ML models on GPUs, TPUs, or NPUs Hands-on expertise with CUDA programming, low-level performance profiling, and compiler-level optimization (TensorRT, TVM, XLA) Experience collaborating with compiler/hardware engineers to bridge model and system-level optimization Excellent problem-solving skills and the ability to debug and tune high-performance inference workloads

Successful hires will work on developing and applying large language models (LLMs) to problems in molecular science and drug discovery. Responsibilities include:

• Scaling and optimizing large model training and inference workflows on cutting-edge DESRES infrastructure
• Pre-training, including designing data pipelines and distributed/parallel training
• Post-training techniques, such as reinforcement learning, contrastive learning, and instruction tuning
• Multimodal learning and integrating non-text modalities (for example, molecular graphs, 3D structures, and time series)

Ideal candidates will have deep expertise in large-scale machine learning systems, LLM architecture and training, and/or multimodal learning, as well as strong Python programming skills. While the application domains include areas such as drug discovery and biomolecular simulation, specific experience in any of these areas is less critical than intellectual curiosity, versatility, and a track record of achievement and innovation in the field of machine learning. For more information, visit www.DEShawResearch.com.

Please apply using the link below:

https://apply.deshawresearch.com/careers/Register?pipelineId=921&source=NeurIPS_1

The expected annual base salary for this position is USD 300,000 - USD 800,000. Our compensation package also includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits, including relocation and immigration assistance. The applicable annual base salary paid to a successful applicant will be determined based on multiple factors including the nature and extent of prior experience and educational background. We follow a hybrid work schedule, in which employees work from the office on Tuesday through Thursday, and have the option of working from home on Monday and Friday.

D. E. Shaw Research, LLC is an equal opportunity employer.

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.