Engineering Manager - Machine Learning Platform

Key Skills

Aartificial intelligence, AWS, Azure, Computer Vision (CV), Deep Learning, Google Cloud Platform (GCP), Infrastructure as code, Leadership Skill, Machine learning techniques, MLOps tools, Natural Language Processing (NLP)

Job Description

Where you will have an impact

• Lead a growing team of 6+ engineers and enabling company wide goals
• Deliver work needed to support all Science teams to train models and run cloud infrastructure efficiently.
• Provide a safe space for the team members to challenge each other and grow in their careers by intentional coaching and development.
• Partner with leadership, program managers and other peer EMs to maintain a culture of collaboration, impact, innovation, and health.
• Ensure goals of the team are aligned to company goals, and the team is set up for success
• Contribute to KPIs and metrics of the team, systems and tooling they provide currently. Intentionally invest in improvements that move the needle on ML engineers’ productivity.
• Provide technical guidance where needed and rely on senior engineers on the team where necessary to make the decisions that drive the team and company forward
• Anticipate the needs of the business 6-24 months out, identify areas where additional resources are needed or we need to grow new domain expertise, and pitch this to leadership for investment

This role will be based in our London King’s Cross HQ, but we are open to discussing hybrid roles for the right candidate.

Challenges you will own

• Developing and training aspects of the model development lifecycle.
• Aligning with customers, and other stakeholders in addition to roadmapping and strategy.
• Creating a dev and training platform where all ML engineers will train their models on.
• Interacting with Azure, cost tracking and optimizations to not only save the company money but also get the performance boosts in model development.

What you will bring to Wayve

Essential

• Prior experience as a manager of MLOps and Infra teams
• Passionate about fostering personal and professional growth in individual team members, building inclusive high performing teams
• Industry experience with embodied AI development with real-world product impact
• Experience with roadmap planning, stakeholder management, requirements gathering and alignment with peers towards milestones and deliverables
• Prior hands-on Cloud Infrastructure and/or MLOps experience

Desirable

• Experience working in a project-based (“matrix”) operating environment
• Bachelors in Computer Science, Engineering, or similar experience (e.g STEM)
• Strong knowledge of Machine Learning and/or Cloud Infrastructure areas, such as Deep Learning, Natural Language Processing, Computer Vision,or Kubernetes, Azure/GCP/AWS etc.

What we offer you:

• The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact
• Competitive compensation and benefits
• A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too
• A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day
• Benefits such as an onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
• This is a full-time role based in our office in London. 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 also operate core working hours so you can be where you need to be for family and loved ones too. Teams determine the routines that work best for them.

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 gender, gender identity, gender expression, race, sexual orientation, physical or mental disability, ethnicity, age or religious belief