- 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 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 have experience with MLOps or ML Infrastructure, reflecting your ability to streamline machine learning workflows.
- 2+ 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.
- Attractive compensation with salary and equity
- Immersion in a team of world-class researchers, engineers and entrepreneurs
- A unique position to shape the future of autonomous driving and to tackle the biggest challenge of our time
- Bespoke learning and development opportunities
- Relocation support with visa sponsorship
- Flexible working hours - we trust you to do your job well, at times that suit you and your team
- Private on-site chef, in-house bar, lots of socials, and more
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Machine Learning Engineer - Mountain View, CA, United States - Wayve Technologies Ltd
Description
Wayve is at the cutting edge of embodied intelligence, developing advanced AI with end-to-end deep learning to navigate the complexities of diverse environments. Our innovative strategy integrates the latest in machine learning, sidestepping conventional methods, to understand and adapt to urban landscapes like never before. We're dedicated to solving one of the most formidable challenges of our time, gathering a diverse team of exceptional minds driven not just by the work but by the opportunity to leave a profound impact on the world through innovative technology.
WHERE YOU'LL HAVE AN IMPACT
Our team is seeking a talented Software 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.
Challenges you will own:
WHAT YOU'LL BRING TO WAYVE
You'd be a great match for this role if:
WHAT WE OFFER YOU
Wayve is built by people from all walks of life. We believe that it is our differences that make us stronger, and our unique perspectives and backgrounds that allow us to build something different. We are proud to be an equal opportunities workplace, where we don't just embrace diversity but nurture it - so that we all thrive and grow.
What sort of compensation are you after? *
