Tech Lead Manager, Machine Learning - Perception

Rivian
London
3 weeks ago
Create job alert

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

We are seeking a Tech Lead Manager (TLM) to lead the evolution and scaling of our perception systems. You will guide a dedicated team in developing and deploying robust machine learning models that enable our vehicles to understand their environment. This role involves cross-functional collaboration, architecting solutions, and driving the technical roadmap to advance our perception technologies.


Responsibilities

As a member of our Autonomy organization, you will guide the strategy, architecture, and deployment of machine learning models for our vehicle's perception. These models support autonomous driving features and in-vehicle experiences by enabling environmental understanding. Your work will directly impact the core functionalities of our autonomous systems.

Key areas of impact include:

  • Technical Strategy & System Architecture: Define and drive the technical vision, architecture, and scaling roadmap for perception systems, ensuring they meet autonomous driving demands and champion new technologies
  • Perception Model Lifecycle Management: Lead the end-to-end development of scalable ML models for critical perception tasks (object detection, tracking, scene understanding, mapping), including MLOps, data pipelines, and optimization for robust onboard deployment
  • Team Leadership & Mentorship: Build, mentor, and lead a high-performing team of machine learning engineers, fostering a culture of innovation, technical excellence, and continuous improvement
  • Cross-Functional Collaboration & Integration: Partner effectively with teams across the autonomy stack (e.g., prediction, planning, simulation, hardware, ML infrastructure) to deliver seamlessly integrated and high-performing autonomous features


Qualifications

  • MS or PhD in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
  • Experience (typically 8+ years post-graduation) in machine learning, computer vision, or robotics, with significant work in perception for autonomous systems
  • Experience (typically 3+ years) in a technical leadership or management role, leading engineering teams on complex projects
  • Technical depth in machine learning, deep learning architectures (e.g., CNNs, Transformers), and computer vision algorithms
  • Experience developing and deploying perception algorithms (e.g., object detection, segmentation, tracking, SLAM, multi-sensor fusion) in real-world applications
  • Proficiency in Python and C++
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and MLOps tools/platforms
  • Communication, interpersonal, and collaboration skills for working in a dynamic, cross-functional environment




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.

Candidate Data Privacy

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 your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law.

Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services.

Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions.

Please note that we are currently not accepting applications from third party application services.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineering Manager

Data Science Manager – Property Tech – London

Principal Data Scientist

Lead Data Engineer (Azure/Databricks)

Data Science Manager

Engineering Manager - MLOps & Analytics

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.