Staff Machine Learning Scientist/Engineer

Socket.dev; Sunnyvale (CA); Hybrid; USD 370,000 - 419,000; Full time

Job summary

Wayve is seeking a Research Scientist to join the MEGA team to advance foundation-model learning for robotics and embodied intelligence. You will contribute to novel architectures, pre-training objectives, and scalable data/training systems, bridging frontier ML with real-world robot evaluation.

You will collaborate with researchers, ML engineers, roboticists, and hardware teams to push robust robot policies and publish impactful results.

Qualifications

• Experience in machine learning with focus on multimodal foundation models.
• Experience with scalable training on large datasets or multi-node setups.
• Strong research track record with publications in top venues.
• Engineering skills and hands-on experience with ML frameworks.
• Ability to design and run rigorous experiments with engineering teams.
• Experience translating research ideas into working systems.
• Strong communication across teams.

Responsibilities

• Research and develop model architectures and data strategies for robot foundation models.
• Develop scalable self-supervised and generative pre-training methods from video data.
• Build distributed training pipelines for large models and data.
• Collaborate with researchers, ML engineers, roboticists and hardware teams.
• Communicate results internally and through publications.

Skills

Multimodal foundation models

Scalable training

ML frameworks

Experiment design

Communication skills

Education

PhD or MS in CS/ML/Robotics

Tools

Python

PyTorch

TensorFlow

Job description

About us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The role

We are looking for a Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science as a founding member.

MEGA is building foundation models for general-purpose robots: models that learn from large-scale video, language, and robot-interaction data, then generalize across tasks and embodiments—including mobile manipulators, dual-arm platforms, and humanoids. Our aim is to build agents that can perceive, reason about, and act reliably in the physical world.

You will help define and build the foundation-model learning stack for robotics: novel model architectures, pre-training objectives, post-training methods, and scalable data and training systems. The work combines frontier ML research with a direct route to real-world evaluation on a growing fleet of robots.

Your work may span vision-language-action models, world and action models, video and multimodal models, imitation learning, reinforcement learning, and self-supervised learning. You will work with large-scale video and robotics datasets and distributed training infrastructure to develop increasingly capable, robust, and general robot policies.

You will collaborate with research scientists, ML engineers, roboticists, and hardware teams to turn promising ideas into large-scale experiments, strong research contributions, and compelling robot demonstrations. This is an opportunity to take meaningful ownership of a new ML-first research program at the frontier of foundation models and embodied intelligence.

Key responsibilities

• Research and develop model architectures, learning objectives, and data strategies for robot foundation models.
• Empirical research experience – experience hill climbing on ML models.
• Experience with various data sources – annotation, filtering, mixing strategies.
• Develop scalable self-supervised and generative pre-training methods using web video, egocentric video, and robot-interaction data.
• Develop post-training approaches—including supervised fine-tuning, imitation learning, reinforcement learning, and related methods—to improve real-world robot capabilities.
• Curate, filter, and evaluate large-scale robotics datasets, including egocentric, UMI, and teleoperated data.
• Build and use distributed training pipelines for large models and large multimodal datasets.
• Work closely with robotics and hardware teams to connect model progress to measurable real-world performance.
• Communicate research clearly internally and, where appropriate, through publications and Wayve’s scientific presence.

About you

In order to set you up for success as a Research Scientist at Wayve, we’re looking for the following skills and experience.

Essential

• Experience in machine learning, with focus in multimodal foundation models and data for foundation models.
• Experience with scalable training, such as multi-node training, large datasets and/or large model training.
• Strong research track record, including publications in top-tier venues such as ICRA, CoRL, CVPR, NeurIPS, ICML or ICLR.
• Strong engineering skills and hands‑on experience with modern machine learning frameworks.
• Ability to design and run rigorous experiments while collaborating closely with engineering and robotics teams.
• Experience translating research ideas into working systems, experiments or deployed capabilities.
• Strong communication skills and the ability to share research clearly across teams

Desirable

• PhD or MS in Computer Science, Machine Learning, Robotics, Computer Vision or a related technical field.
• Industry experience in machine learning, robotics, embodied AI or related applied research environments.
• Experience with real robots, robotic learning, embodied AI, simulation or policy learning.
• Experience working with large-scale video data and sequential decision-making systems.

This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $370,000 to $419,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above.

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

For US candidates only, please visit E-Verify Notice and Participation and Right to Work

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.