NeurIPS 2025 Career Opportunities

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.

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 diseour organization and research partners all for the purpose of contributing to greater understanding of human cell function.

You will have the opportunity to work closely with teams of scientists, computational biologists, engineers and to collaborate with our grantees, with our institutes, and other external labs and organizations. Your work will inspire and enhance the production and analysis of datasets by teams and collaborators. Scientific focus areas could include single cell biology, imaging, genomics, and proteomics.

What You'll Do Working with the AI Research Scientists, iterate on, optimize, deploy, and maintain innovative machine learning models, systems, and software tools that enable the analysis and interpretation of AI models for Biology Work with cross-functional team members to quickly iterate on system performance to meet/stay ahead of users’ needs - e.g. we get feedback that the model doesn't scale to X million so working with our user researcher/scientist/product team to iterate on the solution. Partner with research scientists to build robust data loader pipelines for scalable distributed training and evaluation. Serve as an interface to product and engineering teams to understand how models may need to evolve to support multiple use cases. Develop model evaluation and interpretability frameworks that help biologists understand which data features drive model predictions Build reusable engineering utilities that can unlock experimentation velocity across research initiatives in the organization Optimize model architectures to enhance performance, fine-tune accuracy, and efficiently manage infrastructure resources

What You'll Bring Experience in working with a highly interactive and cross-functional collaborative environment with a diverse team of colleagues and partners solving complex problems through applied deep learning. A track record and expertise in developing deep learning models on large-scale GPU clusters, using techniques of distributing training such as DDP, FSDP, Model parallelism, low-precision training, profiling and optimizing AI/ML code, fine tuning models. Expertise in leading end-to-end experimentation pipelines for training and evaluating deep learning models, with particular focus on experiment tracking and reproducibility. A good working knowledge of Python-based ML libraries and frameworks such as PyTorch, JAX, TensorFlow, NumPy, Pandas, and Scikit-learn. Experience in using modern frameworks for distributed computing and infrastructure management, particularly as related to ML models such as PyTorch Lightning, Deepspeed, TransformerEngine, RayScale etc. Ability to effectively balance exploratory research with robust engineering practices. A good working knowledge of general software engineering practices in a production environment. The ability to work independently and as part of a team, and have excellent communication and interpersonal skills. Have a Masters in computer science with a focus on machine learning & data analytics, or equivalent industry experience and at least 6-8 years of experience developing and applying machine learning methods.

Handshake is building the career network for the AI economy. Our three-sided marketplace connects 18 million students and alumni, 1,500+ academic institutions across the U.S. and Europe, and 1 million employers to power how the next generation explores careers, builds skills, and gets hired.

Handshake AI is a human data labeling business that leverages the scale of the largest early career network. We work directly with the world’s leading AI research labs to build a new generation of human data products. From PhDs in physics to undergrads fluent in LLMs, Handshake AI is the trusted partner for domain-specific data and evaluation at scale. This is a unique opportunity to join a fast-growing team shaping the future of AI through better data, better tools, and better systems—for experts, by experts.

Now’s a great time to join Handshake. Here’s why: Leading the AI Career Revolution: Be part of the team redefining work in the AI economy for millions worldwide. Proven Market Demand: Deep employer partnerships across Fortune 500s and the world’s leading AI research labs. World-Class Team: Leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, just to name a few. Capitalized & Scaling: $3.5B valuation from top investors including Kleiner Perkins, True Ventures, Notable Capital, and more.

About the Role We’re expanding our team and seeking an Engineering Manager to lead the development of high-impact products that empower our Fellows in driving AI innovation. This is a unique opportunity to play a pivotal role in a fast-growing space, working directly with leading AI labs and tech companies to develop solutions that enhance research workflows, model evaluation processes, and domain-specific AI applications. We’re expanding our team and seeking an experienced Engineering Manager to lead our Annotations Team, responsible for building and maintaining the tools that power our data creation pipeline. This team develops products used by operators and fellows to create data used by researchers to train the latest, state of the art language models. As an Engineering Manager, you'll play a key role in shaping technical direction, fostering engineering excellence, and ensuring your team delivers reliable, scalable, and user-centric solutions. You’ll manage a talented group of engineers focused on improving workflow efficiency, quality assurance, and scalability across annotation systems. This is a highly cross-functional role that sits at the intersection of engineering, operations, and product, ensuring our data creation platform is robust, intuitive, and ready to meet evolving research needs.

Location: San Francisco, CA| 5 days/week in-office Lead and grow a high-performing engineering team, fostering a culture of ownership, inclusion, and technical excellence. Partner with product and design teams to define roadmaps, scope projects, and deliver end-to-end solutions aligned with user needs. Drive technical architecture and decision-making, ensuring systems are scalable, maintainable, and performant. Mentor engineers across experience levels, supporting their growth through regular feedback, coaching, and development opportunities. Oversee day-to-day execution, ensuring high-quality code, effective reviews, and healthy team velocity.

Desired Capabilities 2–4+ years of experience in an engineering leadership role (team lead, tech lead, or manager), in addition to prior experience as a hands-on engineer. Strong technical background in full-stack development, particularly with ReactJS, TypeScript, and backend technologies like Node.js or Python. Experience leading teams building end-user products with a focus on quality, usability, and performance. Solid understanding of system architecture, relational databases (e.g., PostgreSQL), and cloud infrastructure (e.g., AWS, GCP). Proven track record of successfully shaping product direction and delivering results in a fast-paced environment. Excellent communication skills

Work Location:

Toronto, Ontario, Canada

Description

We are currently seeking talented individuals for a variety of positions, ranging from junior to senior levels, and will evaluate your application in its entirety.

Layer 6 is the AI center of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs. Our work spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and responsible use of AI. We have access to massive financial datasets and actively collaborate with world renowned academic faculty. We are driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Work with large-scale, real-world datasets spanning multiple modalities, ranging from banking transactions, conversation transcripts to large document collections.

As a Machine Learning Engineer, you will:

• Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge

• Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability

• Write clean, efficient, and maintainable code for ML models to ensure efficient deployment of scalable AI application

• Work with large-scale, real-world datasets that range from banking transactions, conversation histories, to large document collections

• Grow by continuously learning new skills and exploring advanced topics in AI with a team that thrives on knowledge-sharing

Required Qualifications:

• Master or bachelor's degree in computer science, Statistics, Mathematics, Engineering or a related field

• 3+ years of developer experience shipping code in production settings

• Strong background in machine learning and deep learning

• Strong coding proficiency in Python, Java, C, or C++ You value good software design and sweat over details in code and API design

• You take great personal pride in building robust and scalable software

• You are highly accountable and have a strong sense of ownership

• You strive to communicate clearly and with empathy

Preferred Qualifications:

• Research experience with publication record

• Experience with LangGraph, Pytorch, Tensorflow, Jax, or comparable library

• Experience with building and scaling data-intensive software

• Experience using GPUs for accelerated deep learning training

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

Within the Ads Delivery team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. We are looking for a Machine Learning Engineer/Economist with a strong theoretical and data analysis background that understands market design concepts and has the engineering skills to bring them to market. We are looking for an economist who can get their hands dirty and work side by side with other engineers, to advance the efficiency of the Pinterest Marketplace. The nature of projects within this team require a deep understanding of trade-offs, founded on both economic theory and data analysis, from the ideation phase all the way to launch review.

What you’ll do:

• Build statistical models and production systems to improve marketplace design and operations for Pinners, Partners, and Pinterest.
• Tune marketplace parameters (e.g., utility function), optimize ad diversity and load, implement auctions, and model long‑term effects to reduce ad fatigue and improve advertiser outcomes.
• Define and implement experiments to understand long term Marketplace effects.
• Develop strategies to balance long and short term business objectives.
• Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.
• Work across application areas such as marketplace performance analysis, advertiser churn/retention modeling, promotional bandwidth allocation, ranking/pricing/mechanism design, bidding/budgeting innovation, and anticipating second‑order effects for new ad offerings.

What we’re looking for:

• Degree in Computer Science, Machine Learning, Economics, Operations Research, Statistics or a related field.
• Industry experience in applying economics or machine learning to real products (e.g., ads auctions, pricing, marketplaces, or large‑scale recommendation/search systems).
• Knowledge in auction theory, market design, and econometrics with excellent data analysis skills.
• Strong software engineering and mathematical skills and proficiency with statistical methods.
• Experience with online experimentation and causal inference (A/B testing, long‑running experiments, or similar) in large‑scale systems.
• Practical understanding of machine learning algorithms and techniques.
• Impact‑driven, highly collaborative, and an effective communicator; prior ads or two‑sided marketplace experience strongly preferred.

Pittsburgh

We are seeking a part-time Research Assistant in computer vision and machine learning for human behavior analysis and modeling. The successful candidate will investigate new algorithms and models for analyzing and understanding human behavior from video. Specific research topics for human behavior using one or multiple cameras will focus on the design of efficient perceptual algorithms for behavioral cue extraction and novel approaches for the modeling people interaction, with application to medical research and affective computing.

Requirements: - Master or bachelor degree in computer science, applied mathematics, electrical and/or computer engineering with a focus on computer vision/machine learning. - Strong programming skills, Python, Pytorch, Large Vision Models, Multimodal Foundation Models, Transfer Learning. - Three years’ experience in a research environment with at least one year in the designated specialty of research. - Strong interpersonal, verbal, and written communication skills. - Strong organization and planning skills, careful attention to detail with strong follow-through, able to prioritize and organize tasks effectively to accomplish objectives in a timely matter. - Enthusiastic about collaborating with partners from multiple disciplines and institutions.

Stellenbosch University, South Africa

The Department of Mathematical Sciences at Stellenbosch University (South Africa) has a 2-year postdoctoral position available in the area of machine learning for wildlife monitoring and conservation. The project will look at:

zero-shot capabilities of foundation models on challenging real-world datasets typical in African wildlife and environment monitoring (e.g., camera trap imagery);

few-shot learning and generative modelling to deal with these large, unlabelled, long-tailed, noisy image sets.

Applicants must have obtained a PhD degree within the last 4 years, in a field related to the project's themes. The fellowship must commence by 1 March 2026 (preferably sooner).

Applications and supporting documents can be submitted through this online form.

Applications close 15 December 2025.

Enquiries: Prof. Willie Brink (wbrink@sun.ac.za).

Abu Dhabi, UAE

The Department of Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) has faculty openings at all ranks (full/associate/assistant professors). Qualified candidates are invited to apply. Applicants are expected to conduct outstanding research and be committed to teaching. Successful applicants will be provided an attractive remuneration package and allocated generous research funding for each year. Long-term research on big problems is particularly encouraged.

More details about the positions and the submission are available at https://apply.interfolio.com/176242

Those attending NeurIPS are welcome to talk to us to learn more about the university and the positions.

Contact: Chih-Jen Lin (chihjen.lin@mbzuai.ac.ae)

Chicago / Austin

As a Quantitative Research Intern, you will work side-by-side with our Research Team of mathematicians, scientists and technologists, to develop and enhance the models that drive Optiver’s trading. You will tackle a practical research project that has real-world impact and directly influences Optiver’s trading decisions. In our business, where the markets are always evolving, you will use your skills to predict its movements.

What you’ll do: Led by our in-house education team, you will delve into trading fundamentals and engage in a research project that makes a real-world impact. You will be paired with one of Optiver’s seasoned researchers, providing you exposure to a variety of research areas, including: • Using statistical models and machine learning to develop trading algorithms. • Leveraging big data technologies to analyze high-frequency trading strategies, market microstructure, and financial instruments to identify trading opportunities. • Building stochastic models to determine the fair value of financial derivatives. • Combining quantitative analysis and high-performance implementation to ensure the efficiency and accuracy of pricing engines and libraries.

What you’ll get: You’ll join a culture of collaboration and excellence, 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 talented colleagues, collectively tackling some of the toughest challenges in the financial markets.

In addition, you’ll receive: • The opportunity to work alongside best-in-class professionals from over 40 different countries • The opportunity to earn a return internship or full-time offer in Chicago, Austin, New York City, or Amsterdam based on performance • A highly-competitive internship compensation package • Optiver-covered flights, living accommodations, and commuting stipends • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more

Who you are: • Currently enrolled in a PhD program in Mathematics, Statistics, Computer Science, Physics or a related STEM field with outstanding academic performance • Expected graduation between December 2026 and June 2028 • Available to intern during Summer 2026 • Open to full-time opportunities upon graduation in 2027 or 2028 • Solid foundation in mathematics, probability, and statistics • Excellent research, analytical, and modeling skills • Independent research experience • Proficiency in any programming language • Experience in machine learning, with practical applications in time-series analysis and pattern recognition • Strong interest in working in a fast-paced, collaborative environment • Fluent in English with strong written and verbal communication skills

Who we are: At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilising the market no matter the conditions. With a focus on continuous improvement, we prioritise safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe. Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.

Optiver is supportive of US immigration sponsorship for this role.

*We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can reapply once the next recruitment season begins in 2026.

Amsterdam

As a Quantitative Research Intern, you will get to work with our research team of mathematicians, scientists and technologists, to help develop the models that drive Optiver’s trading. You will tackle a practical research challenge that has impact and directly influences Optiver’s trading decisions. In our business, where the markets are always evolving, you will use your skills to predict its movements.

What you’ll do Led by our in-house education team, you will delve into trading fundamentals and engage in research projects that make a real difference. You will enhance your understanding of trading principles and gain hands-on experience by trading on live markets using real Optiver technology, with simulated capital. For the ten-week internship, you will get support from experienced researchers during your research project work, providing you exposure to a variety of areas, including: • Deep dive into trading and research fundamentals, from theoretical concepts to financial markets, strategies and cutting-edge technology • Using statistical models and machine learning to develop trading algorithms • Leveraging big data technologies to analyse trading strategies and financial instruments to identify trading opportunities • Combining quantitative analysis and high-performance implementation to ensure efficiency and accuracy of your models • Gain exposure to various trading and research desks and experience the financial markets first-hand Based on your performance during the internship, you could receive an offer to join our firm full-time after your studies.

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 talented colleagues, working collectively to tackle the toughest problems in the financial markets. In addition, you’ll receive: • A highly competitive internship compensation package • Optiver-covered flights and accommodation in the city centre for the duration of the internship • Extensive office perks, including breakfast and lunch, world-class barista coffee and Friday afternoon drinks • The opportunity to participate in sports and leisure activities, along with social events exclusively organised for your intern cohort

Who you are • Penultimate year student in Mathematics, Statistics, Computer Science, Physics or a related STEM field, with the ability to work full time upon graduation in 2027 • Solid foundation in mathematics, probability and statistics • Excellent research, analytical and modelling skills • Independent research experience • Proficiency in any programming language • Knowledge of machine learning, time-series analysis and pattern recognition is a plus • Strong interest in working in a fast-paced, collaborative environment • Fluent in English with strong written and verbal communication skills

Diversity statement Optiver is committed to diversity and inclusion. We encourage applications from candidates from any and all backgrounds, and we welcome requests for reasonable adjustments during the process to ensure that you can best demonstrate your abilities. Please let us know if you would like to request any reasonable adjustments by contacting the Recruitment team via the contact form, selecting “Reasonable Adjustments” as the subject of your inquiry.

For answers to some of our most frequently asked questions, refer to our Campus FAQs.

For applicants based in India, our entry route is via the placement office internship hiring season (July/August).

*We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can reapply once the next recruitment season begins in 2026.

Location: Aalto University, Finland

Topic: Generative Models, Geometric Deep Learning, Neurosymbolic Methods

Applications: LLMs and Drug Discovery

Ideal background: Strong mathematical/theoretical training, and experience and comfort with programming in deep learning

Contact: Send an email with your CV to Vikas Garg (vgarg@csail.mit.edu)
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