NeurIPS 2025 Career Opportunities

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.

At Pinterest Labs, you'll join a world-class team of research scientists and machine learning engineers to tackle cutting-edge challenges in machine learning and artificial intelligence. This role places you at the intersection of applied research and scalable infrastructure, focusing heavily on ML framework and efficiency.

You will conduct research that can be applied across Pinterest engineering teams, engaging in external collaborations and mentoring. Your research focus will specifically target ML efficiency and large-scale infrastructure challenges within high-impact areas such as: generative recommender systems, post-training, reinforcement learning, multi-modality representation learning, and graph neural networks.

What you’ll do:

• Design, develop, maintain, and enhance advanced machine learning solutions across various key business areas.
• Lead the technical strategy for optimizing and improving the efficiency of large-scale ML infrastructure.
• Lead high-impact machine learning projects, overseeing priorities, deadlines, and deliverables while providing technical guidance.
• Drive alignment and clarity on goals, outcomes, and timelines across teams.

What we’re looking for:

• MS/PhD in Computer Science or a related field degree.
• 10+ years of industry experience.
• Experience in distributed systems, ML frameworks (e.g. PyTorch), and scaling laws.
• Experience in research and in solving analytical problems.
• Cross-functional collaborator and strong communicator.
• Comfortable solving ambiguous problems and adapting to a dynamic environment.

Palo Alto, CA

Position Description: The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI chips tailored to accelerate Tesla’s machine learning capabilities. Their work powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.

Responsibilities: Design, development, and testing of hardware components and systems Work with cross-functional teams to integrate hardware with software and other systems Develop prototypes and proof-of-concepts Influence design decisions through data analysis, provide technical documentation and reports Provide technical documentation and reports

Requirements: Degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field Experience in one of the following areas: AI Accelerators, EDA tools, Physical Design, RTL, DFT, DV, or microarchitecture Strong understanding of hardware design principles and concepts Knowledge and experience with logic design and synthesis tools and techniques Experience with programming languages (e.g., C++, Python, Perl, Linux, MATLAB) Ability to work effectively in a team environment

ABOUT THE ROLE

You would be working as part of our Applied Research team, focused on turning pre-trained LLMs into well-aligned and highly capable AI systems for coding and software development. This is a hands-on role where you'll work across a variety of efforts, including: Building data pipelines for coding use cases, researching and implementing fine-tuning algorithms, training reward models, and more. You will have access to thousands of GPUs in this team.

YOUR MISSION

To turn pre-trained LLMs into well-aligned and highly capable AI systems.

RESPONSIBILITIES

• Research and experiment on ways to specialize foundational models to coding use cases
• Build and maintain data and training pipelines
• Keep up with latest research, and be familiar with state of the art in LLMs, alignment, synthetic data generation, code generation
• Design, analyze, and iterate on training/fine-tuning/data generation experiments
• Write high-quality, pragmatic code
• Work as part of a team: plan future steps, discuss, and communicate clearly with your peers

SKILLS & EXPERIENCE

• Experience with Large Language Models (LLM)
• Deep knowledge of Transformers
• Strong deep learning fundamentals
• Good taste in data
• Fine-tuning experience with LLMs
• Extensively used and probed LLMs, familiarity of their capabilities and limitations
• Knowledge of distributed training
• Strong machine learning and engineering background
• Research experience
• Experience in proposing and evaluating novel research ideas
• Familiar with, or contributed to the state of the art in multiple of the following topics: Fine-tuning and alignment of LLMs, synthetic data generation, continual learning, RLHF, code generation
• Is comfortable in a rapidly iterating environment
• Is reasonably opinionated
• Programming experience: Linux, Strong algorithmic skills, Python with PyTorch or Jax. Use modern tools and are always looking to improve
• Strong critical thinking and ability to question code quality policies when applicable
• Prior experience in non-ML programming, especially not in Python - is a nice to have

PROCESS

• Intro call with one of our Founding Engineers
• Technical Interview(s) with one of our Founding Engineers
• Team fit call with the People team
• Final interview with one of our Founding Engineers

BENEFITS

• Fully remote work & flexible hours
• 37 days/year of vacation & holidays
• Health insurance allowance for you and dependents
• Company-provided equipment
• Wellbeing, always-be-learning and home office allowances
• Frequent team get togethers
• Great diverse & inclusive people-first culture

New York

Software Developer

Technology is integral to virtually everything the D. E. Shaw group does, which is why we seek exceptional software developers with a range of quantitative and programming abilities. Members of our technical staff collaborate on challenging problems that directly impact the firm’s continued success, utilizing their excellent analytical, mathematical, and software design skills as well as some of the most advanced computing resources in the world. Software developers have the opportunity to be part of a collegial, collaborative, and engaging working environment.

What you'll do day-to-day

Specific responsibilities may include formulating statistical models for our computerized trading strategies, developing distributed systems to analyze and react to incoming data in real time, and creating tools for advanced mathematical modeling.

Who we're looking for

• Successful developers have traditionally been the top students in their programs and have extensive software development experience.
• We welcome outstanding candidates at all experience levels.
• The expected annual base salary for this position is 225,000USD. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, a relocation bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

London

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)

Waddle Labs: - we are an early-stage startup - we build robotics models to solve physical bottlenecks in science (eg. wet lab experiments) - YC W26

The other companies on this career site know what they're doing. We don't. Do you want to help us figure it out?

If you want to find out more, reach out to wave@waddlelabs.ai with 1 sentence about what you’re interested in.

We are Bagel Labs - a distributed machine learning research lab working toward open-source superintelligence.

Role Overview

We encourage curiosity-driven research and welcome bold, untested concepts.
You will push the boundaries of diffusion models and distributed learning systems, testing hypotheses at the intersection of generative AI and scalable infrastructure.
We love novel, provocative, and untested ideas that challenge conventional paradigms.

Key Responsibilities

• Prototype AI methodologies that can redefine distributed machine learning.
• Pioneer next-generation diffusion architectures including rectified flows, EDM variants, and latent consistency models that scale across distributed infrastructures.
• Develop novel sampling algorithms, guidance mechanisms, and conditioning strategies that unlock new capabilities in controllable generation.
• Partner with cryptographers and economists to embed secure, incentive-aligned protocols into model pipelines.
• Publish papers at top-tier ML venues, organize workshops, and align our roadmap with the latest academic advances.
• Share insights through internal notes, external blog posts, and conference-grade write-ups (for example, blog.bagel.com).
• Contribute to open-source code and stay active in the ML community.

Who You Might Be

You are extremely curious and motivated by discovery.
You actively consume the latest ML research - scanning arXiv, attending conferences, dissecting new open-source releases, and integrating breakthroughs into your own experimentation.
You thrive on first-principles reasoning, see potential in unexplored ideas, and view learning as a perpetual process.

Desired Skills (Flexible)

1. Deep expertise in modern diffusion models, score matching, flow matching, consistency training, and distillation techniques.
2. Hands-on experience with distributed training frameworks such as FairScale, DeepSpeed, Megatron-LM, or custom tensor and pipeline parallelism implementations.
3. Strong mathematical foundation in SDEs, ODEs, optimal transport, and variational inference for designing novel generative objectives.
4. Clear and concise communication skills.
5. Bonus: experience with model quantization (QLoRA, GPTQ), knowledge distillation for diffusion models, or cryptographic techniques for secure distributed training.

What We Offer

• Top-of-market compensation and time to pursue open-ended research
• A deeply technical culture where bold ideas are debated, stress-tested, and built
• Remote flexibility within North American time zones
• Ownership of work shaping decentralized AI
• Paid travel to leading ML conferences worldwide

Apply now - help us build the infrastructure for open-source superintelligence.

IMC Trading is seeking researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a central ML research team that collaborates across trading teams at IMC. The ideal candidate will have experience working with other researchers and engineers to build and continuously improve models, systems, and research tooling. We firmly believe that success for research-driven efforts lies in bringing together skills in ML, statistics, and trading intuition as well as a problem-solving mindset and pragmatism. This is an opportunity to dive deep into feature engineering and alpha research, and focus on applying a wide range of ML models as well as to perform research on building custom models.

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.

Various locations available

Adobe Researchers are developing the next generation of advanced technologies and user experiences, inventing a future where Adobe enables new forms of creativity, frees people from routine tasks, and allows enterprises to understand and act quickly on customer and business insights. Our research labs are actively published in leading journals and conferences, work with product teams on high profile features, and explore new product opportunities across various domains. We are especially interested in fostering ongoing collaborations that last beyond the internship and become part of your PhD thesis.

Adobe Research focuses on the following research areas: - Content Intelligence - AI & Machine Learning - Computer Graphics (2D&3D) - Data Intelligence - Computer Vision, Imaging & Video - Audio - Systems and Languages - Natural Language Processing - Human Computer Interaction - AR, VR & 360 Photography - Document Intelligence - Intelligent Agents & Assistants

What you will do

Under the direction of an Adobe Research mentor, you will: - Pursue a research problem to apply to Adobe’s products and with the possibility of academic publication - Develop new algorithms, run experiments, and produce demonstration prototypes - Document and present your work, both verbally and in writing

What you will need - Current PhD or master's student in computer science, or related field (exceptional undergraduates will also be considered) - Sufficient research skills and background in your chosen subject area - Strong communication skills and teamwork experience - Passion for solving real-world problems with web-scale data using and inventing innovative Machine Learning algorithms.