NeurIPS 2025 Career Opportunities

Who we are:

Peripheral is developing spatial intelligence, starting in live sports and entertainment. Our models generate interactive, photorealistic 3D reconstructions of sporting events, building the future of live media. We’re solving key research challenges in 3D computer vision, creating the foundations for the next generation of robotic perception and embodied intelligence.

We’re backed by Tier-1 investors and working with some of the biggest names in sports. Our team includes top robotics and machine learning researchers from the University of Toronto, advised by Dr. Steven Waslander and Dr. Igor Gilitshenski.

Our team is ambitious and looking to win. We’re seeking a Machine Learning engineer to develop our motion capture models through synthetic data curation, model training, and inference-time optimization.

What you’ll be doing:

• Developing our data flywheel to autolabel and generate synthetic data,

• Improving our motion capture accuracy by fine-tuning existing models on our domain,

• Optimizing inference time through model distillation and quantization,

What we’d want to see:

• Prior experience with 3D computer vision and training new ML models,

• Strong understanding of GPU optimization methods (Profiling, Quantization, Model Distillation),

• Proficiency in Python and real-time ML inference backends,

Ways to stand out from the crowd:

• Previous experience in architecting and optimizing 3D computer vision systems,

• Strong understanding of CUDA and Kernel programming,

• Familiarity with state-of-the-art research in VLMs,

• Top publications at conferences like NeurIPS, ICLR, ICML, CVPR, WACV, CoRL, ICRA,

Why join us:

• Competitive equity as an early team member.

• $80-120K CAD + bonuses, flexible based on experience.

• Exclusive access to the world’s biggest sporting events and venues,

• Work on impactful projects, developing the future of 3D media and spatial intelligence.

To explore additional roles, please visit: www.peripheral.so

Location: Toronto, ON, Canada

Hong Kong

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)

University of Michigan School of Information Ann Arbor, Michigan, USA

The University of Michigan School of Information (UMSI) invites applications for a faculty position focusing on Artificial Intelligence (AI) Privacy and Ethics at the rank of associate or full professor. Applicants need not have attained tenure elsewhere, but should be prepared to undergo tenure review at University of Michigan as part of the hiring process.

The home for this position will be at UMSI. This is part of a university-level faculty expansion program and collaborative cluster hire in Human-Centered Artificial Intelligence across multiple units; where appropriate, additional affiliations with other units may be considered.

We invite applications from researchers whose work bridges technical and social dimensions of AI systems and applications. We are especially interested in candidates whose scholarship grapples with AI privacy and ethics in the context of legal and regulatory frameworks and/or platform design and governance.

This position offers the opportunity to work in a dynamic, interdisciplinary environment. UMSI faculty collaborate with colleagues across campus, for example at the Law School, the Ford School of Public Policy, and the College of Engineering, and have founded initiatives such as the U-M Center for Ethics, Society, and Computing (ESC). This position offers the opportunity to work at the cutting edge of human-centered AI research while joining a community of scholars dedicated to advancing impactful and socially responsible scholarship.

The anticipated starting date for this appointment is August 25, 2026.

Job responsibilities include research, teaching, and service. Job responsibilities include but are not limited to: Conduct scholarly research resulting in publications in peer-reviewed journals, book chapters, edited books, books, and conference proceedings; Seek external funding to support their research program; Teach in UMSI’s five academic programs; Mentor students for independent studies, master’s projects and theses, and doctoral dissertations; Provide service to the school, the university, and the broader academic community, for example through committee work, journal editing, community engagement, and other opportunities.

Each contributing member of the UMSI tenure-track faculty maintains a teaching effort equivalent to three semester-long courses per year.

Qualifications: Ph.D. in information, computer science, social science, or other appropriate disciplines Demonstrated ability for exemplary teaching at the undergraduate and/or graduate levels; Demonstrated ability for scholarly impact in research; A strong commitment to interdisciplinary research.

All applicants for this position should submit a cover letter, a vita, three representative publications, evidence of teaching excellence if available, a statement of current and future research plans, statement of teaching philosophy and experience, and the names of three recommenders. All application materials must be submitted electronically to: https://apply.interfolio.com/172854.

Consideration of applications will begin immediately. Applications must be submitted by November 15, 2025, as the job posting will close for review on that date. Please direct inquiries about this position to SISearchSupport@umich.edu.

Employment will require both a criminal background check and an institutional reference check regarding any misconduct. Candidates will be required to submit a self-disclosure form as well as an authorization to release information form.

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.

The University of Michigan is an equal employment opportunity employer.

Hong Kong

Flow Traders is committed to leveraging the most recent advances in machine learning, computer science, and AI to generate value in the financial markets. We are looking for Quantitative Researchers to join this challenge.

As a Quantitative Researcher at Flow Traders, you are an expert in mathematics and statistics. You are passionate about translating challenging problems into equations and models, and have the ability to optimize them using cutting-edge computational techniques. You collaborate with a global team of researchers and engineers to design, build, and optimize our next generation of models and trading strategies.

Are you at the top of your quantitative, modeling, and coding game, and excited by the prospect of demonstrating these skills in competitive live markets? Then this opportunity is for you.

Successful hires will support our machine learning team by processing and organizing scientific datasets relevant to drug discovery and development. Candidates should have an undergraduate degree in a STEM field, hands-on experience in a Linux environment, and familiarity with Python and SQL. Experience handling large-scale datasets, structuring data from diverse sources, and cataloging metadata to facilitate data discovery and maintain accurate data provenance is highly desirable. This is a two-year position with full benefits. For more information, visit www.DEShawResearch.com.

Please apply using the link below:

https://apply.deshawresearch.com/careers/Register?pipelineId=909&source=NeurIPS_1

The expected annual base salary for this role is USD 160,000 - USD 200,000. Our compensation package includes variable compensation in the form of sign-on and year-end bonuses, as well as generous benefits, including relocation and immigration assistance. The final salary will be determined based on multiple factors, including prior experience and educational background. We follow a hybrid work schedule, with employees working in-office from Tuesday through Thursday and having the option to work remotely on Monday and Friday.

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

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.

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!

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. We are looking for a DL Research Group Lead to drive cutting-edge AI research and lead a core DL subgroup. As DL becomes a central engine of the business, your team’s impact will grow across major markets and asset classes.

Responsibilities:

• Lead development of AI models, especially foundational models for market data, to predict prices in noisy, fast-changing markets;
• Set the research agenda, design experiments, and validate results;
• Build and manage a high-performing research team;
• Ensure a fast, transparent, value-driven research process;
• Integrate contributions from multiple researchers into production-ready solutions;
• Contribute hands-on to coding and strategy development;
• Expand responsibilities within the DL department over time.

Requirements:

• Strong DL researcher with technical leadership experience;
• Preferably experienced in high-end AI domains (LLMs, reasoning, generative models);
• Motivated by deep research and real-world impact;
• Able to maintain high pace while supporting a healthy team culture;
• Trading experience optional — first-principles thinking is key.

What we offer:

• Relocation package to Amsterdam
• High impact on a core business function and direct influence on real PnL;
• Minimal bureaucracy, fast feedback loops, massive datasets, reproducible experiments;
• Strong engineering support and an H200-based Data Center growing 2× yearly;
• Work on extremely challenging, non-stationary markets with low signal-to-noise;
• Opportunity to build foundational models for finance and shape the future of quant AI;
• Freedom to pursue deep research and define your modeling vision;
• A top-tier team, on-site in Amsterdam, working directly with founders;
• Influence over team hiring and development.
• Internal training, comprehensive health insurance, sports reimbursement, and biannual corporate events

New York / Chicago

Flow Traders is committed to leveraging the most recent advances in machine learning, computer science, and AI to generate value in the financial markets. We are looking for Quantitative Researchers to join this challenge.

As a Quantitative Researcher at Flow Traders, you are an expert in mathematics and statistics. You are passionate about translating challenging problems into equations and models, and have the ability to optimize them using cutting-edge computational techniques. You collaborate with a global team of researchers and engineers to design, build, and optimize our next generation of models and trading strategies.

Are you at the top of your quantitative, modeling, and coding game, and excited by the prospect of demonstrating these skills in competitive live markets? Then this opportunity is for you.

Global

Description

Qualcomm is proud to be attending NeurIPS 2025 in our home city San Diego, California! Qualcomm is powering efficient AI from edge to cloud, conducting novel foundational, platform, and applied AI research to enable intelligent computing everywhere.

We're inviting all those who have a passion for AI and are interested in opportunities in generative AI, visual AI, computer vision, and foundational machine learning to please follow the steps below.

1. Go to our Qualcomm - NeurIPS home page.

2 .Register by clicking on the blue link. This allows us to identify your application as someone we met at NeurIPS.

1. Apply to any of the linked positions below. Make sure you REGISTER first before applying. Your resume will stand out.