资深 / 高级机器学习工程师，强化学习

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

As a Senior / Staff Machine Learning Engineer in Wayve's AV Core organisation, you will advance reinforcement learning methods for end-to-end driving models. You will identify where learning from reward or feedback can improve beyond behavior cloning, then take promising ideas from design through large-scale experiments, rigorous evaluation, and integration into our best driving models.

Driving Core team develops the learning methods that turn diverse driving data into robust closed-loop behavior. You will be a technical owner for reinforcement learning within the group, working closely with researchers and engineers across AV Core, Simulation, Evaluation, and Product Engineering. Success means producing measurable improvements in driving behavior.

Core Model Safety team develops the core model competencies that enable safe, driverless operation. You will lead the technical direction and delivery of a learned emergency trajectory model for low-frequency, high-consequence maneuvers such as evasive steering and emergency braking. You will take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.

Key responsibilities

• Shape and execute the reinforcement learning roadmap for Driving Core / Core Model Safety, selecting problems and methods against clear behavioral gaps and measurable success criteria.

• Develop and evaluate post-behavior-cloning optimization methods, including offline and off-policy reinforcement learning as well as other reward-guided approaches; design the regularization, data strategy, and diagnostics needed to make policies reliably better.

• Help improve the reward models and related learning signals used to train and evaluate driving policies, working with partner teams to strengthen their quality, scalability, and downstream usefulness.

• Build robust training and experimentation workflows using large-scale driving data; diagnose distribution shift, objectiv

As a Senior / Staff Machine Learning Engineer in Wayve's AV Core organisation, you will advance reinforcement learning methods for end-to-end driving models. You will identify where learning from reward or feedback can improve beyond behavior cloning, then take promising ideas from design through large-scale experiments, rigorous evaluation, and integration into our best driving models.

Driving Core team develops the learning methods that turn diverse driving data into robust closed-loop behavior. You will be a technical owner for reinforcement learning within the group, working closely with researchers and engineers across AV Core, Simulation, Evaluation, and Product Engineering. Success means producing measurable improvements in driving behavior.

Core Model Safety team develops the core model competencies that enable safe, driverless operation. You will lead the technical direction and delivery of a learned emergency trajectory model for low-frequency, high-consequence maneuvers such as evasive steering and emergency braking. You will take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.

• Shape and execute the reinforcement learning roadmap for Driving Core / Core Model Safety, selecting problems and methods against clear behavioral gaps and measurable success criteria.

• Develop and evaluate post-behavior-cloning optimization methods, including offline and off-policy reinforcement learning as well as other reward-guided approaches; design the regularization, data strategy, and diagnostics needed to make policies reliably better.

• Help improve the reward models and related learning signals used to train and evaluate driving policies, working with partner teams to strengthen their quality, scalability, and downstream usefulness.

• Build robust training and experimentation workflows using large-scale driving data; diagnose distribution shift, objective misspecification, optimization instability, and data or evaluation bias.

• Define evidence across offline metrics, open-loop tests, closed-loop simulation, and on-road evaluation, and distinguish genuine policy improvement from benchmark overfitting.

• Productionize successful methods in the shared ML stack, communicate decisions and results clearly, and raise the technical bar through design reviews, code reviews, and mentoring.

In order to set you up for success as a Staff / Senior Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.

• A strong track record developing and experimentally validating reinforcement learning or closely related sequential decision-making methods on complex, high-dimensional problems.

• Deep understanding of modern reinforcement learning fundamentals, including policy and value learning, off-policy learning, function approximation, distribution shift, and the failure modes of learned objectives.

• Hands-on experience with behaviour cloning, reinforcement learning, or related methods.

• Proficiency in Python and PyTorch, with strong software engineering practices and hands-on experience building reliable machine learning training and evaluation systems.

• Excellent experimental judgement: able to turn an ambiguous behavioral problem into falsifiable hypotheses, useful metrics, disciplined ablations, and clear technical decisions.

• Senior-level ownership and collaboration: able to lead a substantial technical area, work across research and engineering boundaries, and bring others along through clear written and verbal communication.

Desirable

• Experience with offline reinforcement learning, imitation learning, reward modeling, preference learning, or post-training of large neural policies.

• Experience in autonomous vehicles, robotics, control, or another domain where policies interact with safety-critical physical systems, including an understanding of motion planning, vehicle dynamics, control, or collision avoidance.

• Experience with closed-loop simulation, off-policy evaluation, uncertainty or calibration, and evaluation under rare or shifted conditions.

• Experience training multimodal, transformer-based, or generative policy models at scale.

• Proficiency in C++, CUDA, distributed training, or performance optimization for production machine learning systems.

This is a full-time role based in our office in Sunnyvale. 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. The reasonably estimated salary for this role ranges from $ 311,850 to $ 389,400, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

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.