NeurIPS 2025 Career Opportunities

Toronto or remote

Mission: We are seeking a highly skilled Machine Learning Engineer to join our advanced model development team. This role focuses on pre-training, continued training, and post-training of models, with a particular emphasis on draft model optimization for speculative decoding and quantization-aware training (QAT). The ideal candidate has deep experience with training methodologies, open-weight models, and performance-tuning for inference.

Responsibilities & opportunities in this role: Lead pre-training and post-training efforts for draft models tailored to speculative decoding architectures. Conduct continued training and post-training of open-weight models for non-draft (standard) inference scenarios. Implement and optimize quantization-aware training pipelines to enable low-precision inference with minimal accuracy loss. Collaborate with model architecture, inference, and systems teams to evaluate model readiness across training and deployment stages. Develop tooling and evaluation metrics for training effectiveness, draft model fidelity, and speculative hit-rate optimization. Contribute to experimental designs for novel training regimes and speculative decoding strategies.

Ideal candidates have/are: 5+ years of experience in machine learning, with a strong focus on model training. Proven experience with transformer-based architectures (e.g., LLaMA, Mistral, Gemma). Deep understanding of speculative decoding and draft model usage. Hands-on experience with quantization-aware training, including PyTorch QAT workflows or similar frameworks. Familiarity with open-weight foundation models and continued/pre-training techniques. Proficient in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.

Preferred Qualifications: Experience optimizing models for fast inference and sampling in production environments. Exposure to distributed training, low-level kernel optimizations, and inference-time system constraints. Publications or contributions to open-source ML projects.

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

Austin, TX

About the Team

Avride builds autonomous solutions from the ground up, using machine learning as the core of our navigation pipeline. We are evolving our stack to support the next generation of self-driving, leveraging efficient CNNs, Transformers, and MLLMs to solve complex perception and planning challenges. Our goal is to apply the right approach to the right problem, laying the groundwork for unified, data-driven approaches.

About the Role

We are seeking a Machine Learning Engineer to build the infrastructure and ML foundations for advanced autonomous behaviors. You won't just optimize isolated models; you will architect scalable training workflows and high-fidelity components.

This is a strategic position: You will contribute to the critical infrastructure that paves the way for future end-to-end capabilities. You will translate relevant research ideas into production-ready improvements when they prove beneficial, helping prepare our stack for a transition toward unified, learned behaviors.

What You'll Do

• Strengthen Core Modules: Design and refine models for perception, prediction, or planning, enhancing reliability to support future holistic learning approaches.
• Architect Data Foundations: Build scalable pipelines for multimodal datasets, ensuring they support both current needs and future large-scale E2E experiments.
• Advance Training Infra: Develop distributed training workflows capable of handling massive model architectures for next-gen foundation models.
• Bridge Research & Production: Analyze research in relevant fields, identifying specific opportunities to introduce these techniques into our production stack.
• System Integration: Collaborate with engineering teams to ensure individual ML improvements translate into better system-level performance.

What You'll Need

• Strong ML Fundamentals: Mastery of processing and fusing self-driving modalities (multiview camera, sparse LiDAR, vector maps).
• Architectural Expertise: Deep knowledge of modern architectures like Transformers and Attention Mechanisms.
• Applied Experience: 5+ years of combined experience in industry or applied research settings, with a strong grasp of the full lifecycle from data to deployment.
• Technical Proficiency: Python, PyTorch/JAX/TensorFlow, and distributed computing (PySpark, Ray).
• Systems Mindset: Ability to visualize how modular systems evolve into end-to-end learners and the practical challenges of deploying them.
• Research Capability: Ability to distill complex papers into practical engineering roadmaps.

Nice to Have

• Advanced degree in CS, ML, Robotics, or related field.
• Familiarity with World Models, Occupancy Networks, or Joint Perception-Planning.
• Experience with inference optimization (Triton, TensorRT) and embedded hardware.

San Jose, CA, USA

Adobe is looking for a Senior Software Engineer to contribute to building the platform that powers Adobe Experience Platform’s Generative AI capabilities. Partnering with other business units, you will be building products that transform the way companies approach audience creation, journey optimization, and personalization at scale. You will join a diverse, lively group of engineers and scientists long established in the ML space. The work is dynamic, fast-paced, creative, collaborative and data-driven.

What you'll Do - Architect solutions to implement functionality across multiple services and teams.
- Design and build solutions for comprehensive monitoring and alerting of anomalies.
- Design and build highly available services that scale horizontally - Participating in all aspects of software development activities, including design, coding, code review, unit/integration/end-to-end testing, refactoring, bug fixing, and documentation
- Work in multi-functional teams to ensure timely delivery of high-quality product features
- Fast prototyping of ideas and concepts and researching the latest industry trends.
- Experiment with upcoming technologies in a fast-paced environment.

What you need to succeed The ideal candidate will have the following background: - Bachelor's degree or higher in Computer Science, or equivalent experience in the field. - 10+ years of experience in web technologies - Proven programming skills with extensive experience in languages such as Java and Python. - A proven expertise building large scale distributed systems - Experience in building, deploying, and managing infrastructures in public clouds (Azure / AWS)
- Ability to demonstrate a high level of ownership for the entire SDLC, including designing, building, testing, deploying, and supporting production microservices in a fast-paced environment.
- Strong problem-solving and analytical abilities.
- Be a self-starter requiring minimal direction with ability to learn quickly and adapt to changing priorities and requirements. - Accept challenges outside one's comfort zone and deliver viable solutions within defined time boundaries.
- Ability to think through solutions from a short term and long-term lens in an iterative development cycle. - A dedication to learning and sharing ideas with your fellow engineers - Mastery of breaking down, discussing, and communicating abstract technical concepts - Familiarity with agile development methodologies - Real world experience working with Generative AI - Worked on Machine Learning infrastructure and applications

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 an key enabler for the smart vehicle transformation and commercialization with our integrated solutions deployed at scale.

The Silicon Valley Research Lab focuses on developing novel algorithms and technologies to allow machines to learn new knowledge and skills as efficient as human. We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL), etc.

As a Research Scientist in the team, you will conduct research within a specialized focus area and collaborate with internal and external world-class researchers and applied engineering teams.

• Propose and formulate research problems towards solving AGI
• Design, implement and evaluate algorithms, models and prototypes of AI systems
• Collaborate with team members to achieve research goals
• Report and present research findings internally and externally (such as in top tier academic journals and/or conferences)

Here is what we’d like to see in you:

• PhD degree ((or close to completion)) in computer science, machine learning, robotics, or related field, with a broad knowledge of machine learning approaches and theory
• Track record of coming up with and implementing new ideas in AI
• Strong ability in mathematically modeling real world problems
• Strong ability in implementing algorithms and systems
• Hunger for learning new things
• Passion in artificial general intelligence and willingness to do challenging deep research
• Experience in one or more fields of artificial intelligence such as machine learning, natural language processing, computer vision, reinforcement learning, robotics, large language models, etc.
• Applicants must be able to obtain work authorization in the U.S. at the time of hire, and maintain ongoing work authorization during employment.

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 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.

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)

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 research centre 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 research broadly 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 always looking for people driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.

As a Research Machine Learning Scientist, you will

• Join a world-class team of machine learning researchers with an extensive track record in both academia and industry.

• Research, develop, and apply new techniques in deep learning to advance our industry leading products.

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

• Collaborate closely with our engineering team in a fast-paced startup environment and see your research deployed in production with very short turnaround.

Required Qualifications:

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field

• Strong background in machine learning and deep learning

• 2+ years of research experience with publication record

• Proven track record of applying machine learning to solve real-world problems

Preferred Qualifications:

• Depth of experience in relevant ML research disciplines

• Hands on experience in software systems development

• Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library

• Experience with Spark, SQL, or comparable database systems

• Experience using GPUs for accelerated deep learning training

• Familiarity with cloud computing systems like Azure or AWS

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.

We are seeking a highly motivated and talented researcher to work on various aspects of AI safety, trust, and alignment in Fujitsu Research of America. We value individuals with a vision to pick up new knowledge, see through complex scenarios and arrive at simple, elegant yet workable solutions. Self-driven nature, creativity, communication skills, and attention to details are traits of a successful researcher in this role.

Job responsibilities: Conduct research on developing novel algorithms in enhancing AI safety such as for a) countering deepfakes b) detecting and mitigating misinformation and disinformation, c) LMM alignment across cultures, d) agent safety check and agent guardrail and so on Conduct experiments and data analysis to evaluate the effectiveness of research findings on synthetic simulations and real world applications Publish findings in renowned scientific journals and conferences, while also showcasing achievements through invited talks and industry events Integrate various stages of technologies from early stage in-house developed to commercially available software to deliver impactful solutions in the real world

Essential requirements: PhD in Computer Science or a related field Strong track record of publishing research in top-tier conferences and journals in AI, ML, CV, NLP, RL, HCI, etc. Expert-level knowledge and extensive experience in two or more of these areas: Generative AI (LLM, VLM, LMM, and AI agents), AI safety and alignment, Fair and trustworthy ML, Reinforcement learning, Deep learning, Privacy-preserving ML, Causal ML Proficiency in AI/ ML programming-Proven experience in rapid prototyping and testing methodologies to validate the functionality and performance of developed solutions Excellent oral and written communication skills US Work authorization

Interested candidates may contact Ramya Srinivasan at the conference

Location: Palo Alto, CA

Description: Salesforce AI Research is seeking a forward-thinking and accomplished Applied Scientist with deep expertise in AI fairness, accountability, transparency, and explainability (FATE). In this high-impact role, you will operate at the forefront of responsible AI development, working closely with research scientists and engineers in AI Research, as well as cross-functional partners in Responsible AI, Agentforce, and other teams across Salesforce.

You will lead the design and implementation of Trust Layer models, as well as RAI tools and frameworks that ensure our AI systems are fair, accountable, and transparent. Using advanced machine learning techniques, you’ll generate actionable insights, drive research excellence, and support responsible AI practices across the full development lifecycle—from experimentation to production deployment.

We’re looking for a principled and collaborative thought leader who is passionate about bridging the gap between innovation and ethical implementation. You will engage with interdisciplinary teams, strategic partners, vendors, and customers while upholding Salesforce’s core values: trust, customer success, equality, innovation, and sustainability.

Check out our website to learn more about the Salesforce AI Research team https://www.salesforceairesearch.com

Job Responsibilities:

Build state-of-the-art LLM safeguards for enterprise.

Analyze data and models to identify potential trust and safety issues; define testing protocols for different data types and model architectures; recommend mitigation strategies, tooling investments, and safe thresholds for deployment.

Define technical goals and guide research/engineering teams on responsible AI best practices. Offer development support and thought leadership on critical ethical tradeoffs in algorithmic design.

Contribute to the development and adoption of libraries and tools that support evaluation, testing, and mitigation of risks. Build features that enhance explainability and user trust in model outputs.

Collaborate with industry leaders in similar positions in peer organizations on ways to improve the state of responsible AI development.

Minimum Qualifications:

Practical experience in machine learning

MS or Ph.D. in a quantitative discipline with 3+ years of industrial experience, or a BS in a quantitative discipline with 5+ years of industrial experience.

Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets.

Proficient in using Python and common machine learning frameworks (e.g., TensorFlow, PyTorch) and AI tools to implement models and algorithms.

Up to date on the evolution of trusted AI and ability to meet both state-of-the-art and global standards for evaluation, particularly in generative AI.

Experience working across teams of engineers, data scientists, and researchers.

Strong communication skills. Comfortable presenting ideas to peers, cross-functional groups, and executives in multiple formats, from slide decks to informal chats.

Builds trusted relationships across all levels, both internally and externally. Thoughtfully challenges the status quo to enhance team productivity, effectiveness, and culture while maintaining strong, positive partnerships.

Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems.

Demonstrated experience with actually shipping code, getting data science into production.

Passion for the idea that technology can be a force for social good and for ethics and fairness.

Preferred Qualifications:

Strong experience leading multi-disciplinary teams driving significant business results.

Knowledge of enterprise SaaS space.

Experience with designing and building micro-services, familiar with Kubernetes/containerization/RESTful API/gRPC, etc.

Proficient in SQL, shell scripting, and Unix/Linux command-line tools.

Strong publications at top AI conferences.

The role We are seeking a highly skilled and customer-focused professional to join our team as a Cloud Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work remotely from the US or Canada.

Your responsibilities will include: - Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices. - Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers. - Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI. - Act as a single point of expertise of customer scenarios for product, technical support, marketing teams. - Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: - 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing - Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python - Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL) - Excellent communication skills - Customer-centric mindset

It will be an added bonus if you have: - Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow) - Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch) - Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google)