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Tech Lead - Manager - ML training and infrastructure, Autonomy

Job in Camden Town, Camden, Greater London, N1C, England, UK
Listing for: Rivian Automotive
Apprenticeship/Internship position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 180000 GBP Yearly GBP 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: Camden Town

About Rivian

Rivianis on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.

As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

Role Summary

As a Tech Lead - Manager - ML training and infrastructure, you will be a member of the Perception team at Rivian, which develops advanced machine learning algorithms that directly impact safety critical self-driving features of our category defining vehicles.

We are looking for candidates with deep knowledge and strong enthusiasm towards establishing a state-of-art ML infrastructure for training and inference of large autonomous driving models; and optimizing the training and inference performance

Responsibilities
  • Optimize the performance of Deep Learning training workload on NVIDIA GPU systems on a large scale
  • Optimize the latency of model inference and model pre- and post-processing on onboard systems
  • Design, train, and deploy large deep learning models that can leverage the vast amount of labeled and unlabeled data
  • Drive architectural decisions, design reviews, and engineering standards across the team to ensure scalability, security, and maintainability.
  • Identify technical dependencies and operational bottlenecks early, unblocking team members to maintain high execution momentum.
  • Establish and enforce team guidelines for code reviews, testing, deployment, and operational excellence.
Qualifications
  • PhD in CS/CE/EE, or equivalent, in industry experience
  • Deep knowledge of PyTorch, Trensor Flow or Jax
  • Knowledge of model training framework
  • In-depth knowledge of transformer architecture and ways to accelerate the training and inference of transformer models
  • Experience of performing large scale distributed training of models
  • A track record of profiling models and doing detective work to improve model training and inference speed
Equal Opportunity

Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.

Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candi

Candidate Data Privacy and Technology

Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes ("Candidate Personal Data"). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system;

(ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and…

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