Senior Machine Learning Engineer

Wayve; London; On-site; GBP 65,000 - 100,000; Full time

Job summary

Wayve is seeking a Machine Learning Engineer to advance its AI technology for automated driving. In this role, you'll work collaboratively on projects that enhance system performance and reliability while contributing to the development of cutting-edge AI applications. Ideal candidates have substantial experience in engineering practices and thrive in dynamic environments, pushing the boundaries of research and development.

Qualifications

• 7+ years of experience in a relevant field.
• Experience in system design and architecting robust solutions.
• Proficiency in Python or a systems/backend programming language.

Responsibilities

• Collaborate with Applied Scientists on embodied Foundation Models.
• Develop datasets and data engineering pipelines.
• Drive performance optimizations and ensure system reliability.

Skills

Problem Solving

Python

MLOps

Collaboration

Education

BS or MS in Computer Science, Engineering, or related discipline

Job description

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.
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!

About the Role

Our team is seeking a talented Machine Learning Engineer to propel our ambitious research forward. We're not just another team; we're a dynamic blend of Applied Scientists, Machine Learning Engineers, and Software Engineers united together to apply state of the art research to the road. From pioneering advancements in Offline Reinforcement Learning (RL) and Reward Learning from Human Feedback (RLHF) to developing groundbreaking, large-scale, embodied Foundation Models, our projects are designed to dramatically enhance our product's capabilities. But it's not just about what we do-it's how we do it. We believe in the power of cross-functional collaboration, rigor in engineering, and a relentless pursuit to innovate.

In this role, you might:

• Collaborate with Applied Scientists and Machine Learning Engineers on advanced, multimodal, embodied Foundation Models, enhancing your Machine Learning Engineering (MLE) skills.
• Develop and manage comprehensive datasets and data engineering pipelines, supporting complex research initiatives.
• Craft and refine tools for rapid exploration and detailed visualizations, pushing the boundaries of research efficiency.
• Drive observability, monitoring, and performance optimizations to elevate system reliability and performance.
• Create tools specifically designed to expedite solving research problems, showcasing your problem-solving capabilities.
• Work seamlessly with platform teams, facilitating integration and leveraging shared resources for broader impact.

You'd be a great match for this role if:

• You champion engineering best practices, ensuring solutions are scalable, efficient, and maintainable. You prioritize code quality, readability, and reusability, understanding that these qualities are key to long-term success.
• You excel in ambiguous, fast-paced environments, adept at navigating and thriving amidst change.
• You get excited about optimizing pre-training runs, for example, including data pre-processing, CUDA optimization, model quantization and optimization, increasing throughput of training jobs (e.g., FP-8).
• (A plus) You have experience with MLOps or ML Infrastructure, reflecting your ability to streamline machine learning workflows.

Essentials:

• 7+ years of experience with a BS or MS in Computer Science, Engineering, or related discipline, or equivalent experience.
• Solid experience with Python or proficiency in a systems/backend programming language with the ability to quickly adapt to Python.
• Demonstrated experience in system design, capable of architecting robust, scalable solutions.
• Proven track record of working in teams to successfully deliver open-ended projects.
• Ability to work cross-functionally, bridging gaps between teams to drive collective goals

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.

For more information visit Careers at Wayve.

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

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.