Principal Machine Learning Engineer
Description For Principal Machine Learning Engineer
Founded in 2017, Wayve is the leading developer of Embodied AI technology for autonomous driving. We're seeking a Principal Machine Learning Engineer to join our Embodied AI division, working on modelling, robotics, data, and detectives teams to deliver an Autonomous Driving product.
In this role, you'll lead at least one company-wide program, develop and implement machine learning models and robotics systems, collaborate with cross-functional teams on strategy, and contribute to the growth and mentorship of junior engineers. You'll be responsible for enhancing our Autonomous Vehicle stack, troubleshooting and optimizing machine learning models, and fostering a culture of collaboration and innovation.
Key responsibilities include:
- Technical leadership of company-wide programs
- Developing ML models and robotics systems for autonomous driving
- Collaborating on company strategy and roadmap
- Mentoring junior engineers
- Optimizing resource allocation
- Fostering a collaborative and innovative culture
- Evaluating project decisions and analyzing risks
- Troubleshooting and optimizing ML models and systems
Requirements:
- 7+ years of software and machine learning engineering experience
- Strong insight into practical aspects of deep learning
- Passion for impactful research
- Good grasp of machine learning literature
- Experience with large quantities of image and video data
- BSc or higher in ML, CS, Engineering, or related field
Desirable skills:
- Strong software engineering in Python, C++, CUDA
- Experience in computer vision, robotics, simulation, graphics, or large language models
- MS or higher in relevant field
Wayve offers a dynamic work environment, competitive compensation, and benefits such as an onsite chef, workplace nursery scheme, private health insurance, and more. We operate a hybrid working policy, combining office time with remote work. Join us in shaping the future of autonomous driving!
Responsibilities For Principal Machine Learning Engineer
- Technical leadership of at least one company wide program
- Developing and implementing machine learning models and robotics systems to enhance the capabilities of our Autonomous Vehicle stack
- Collaborating with cross-functional teams to contribute to the broader company strategy and roadmap, focusing on machine learning applications
- Enhancing skills and knowledge in machine learning through continuous learning and application, while contributing to the growth and mentorship of junior engineers
- Allocating personal bandwidth and technical resources effectively to meet both project requirements and personal professional development needs
- Working with leadership and other teams to foster a culture that promotes collaboration, high impact, innovation, and a healthy work environment
- Evaluating project decisions and outcomes, identifying dependencies, and analysing risks associated with machine learning deployments
- Troubleshooting and optimising machine learning models and systems - identify potential issues, challenge existing assumptions, introduce innovative solutions, and implement feedback loops to enhance model performance
Requirements For Principal Machine Learning Engineer
- 7+ years of software and machine learning engineering experience in an industrial or applied research environment
- Good insight into the practical aspects of training, validation, testing and metrics for deep learning features/models
- Passion to work in a team on research ideas that have real product impact
- A good grasp of machine learning literature, ideally published
- Comfortable working with large quantities of image and video data
- BSc above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience
Benefits For Principal Machine Learning Engineer
- Competitive compensation and benefits
- Dynamic and fast-paced work environment
- Learning opportunities from bright minds in the field
- Ego-free and respectful culture
- Onsite chef
- Workplace nursery scheme
- Private health insurance
- Cycle scheme
- Therapy
- Yoga
- Two onsite bars
- Large social budgets
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