Sr. Manager, Hardware, Machine Learning/AI

Sr. Manager, Hardware, Machine Learning/AI

Full-Time 63000 - 77000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead the development of machine learning workflows for cutting-edge AI platforms.
  • Company: Join Rivian, a trailblazer in emissions-free electric vehicles.
  • Benefits: Enjoy competitive pay, health perks, and opportunities for remote work.
  • Other info: Be part of a diverse team passionate about adventure and sustainability.
  • Why this job: Make a real impact in AI while working with innovative technology.
  • Qualifications: Experience in machine learning systems and team leadership is essential.

The predicted salary is between 63000 - 77000 £ per year.

About Us

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.

Responsibilities

  • Direct the development and strategy of machine learning enablement workflows for Rivian edge AI platforms.
  • Oversee the roadmap for front-end compiler and model-ingestion tooling to support an expanding model zoo on RAP1 and future platforms.
  • Drive the architectural vision for robust quantization-aware training and model optimization infrastructure at scale.
  • Manage the end-to-end process of porting, optimizing, and benchmarking machine learning models for hardware accelerators and NPUs.
  • Lead cross-functional initiatives with hardware and systems teams to optimize performance across memory, scheduling, and data-movement constraints.
  • Establish rigorous standards and methods for evaluating model fidelity and deployment quality across diverse execution paths.
  • Collaborate with executive leadership to identify highest-value workloads and align technical execution with Rivian's product milestones.
  • Recruit, mentor, and grow a world-class team of engineers specializing in model deployment, compiler infrastructure, and hardware-aware ML.
  • Help shape the long-term direction of Rivian’s edge AI stack, including support for increasingly large and complex neural network models.

Qualifications

Qualifications

  • Proven experience leading or managing teams in machine learning systems, model deployment, or AI infrastructure.
  • Strong background in model optimization for edge or accelerated inference, including quantization and performance tuning.
  • Experience building or extending compiler, toolchain, or graph-transformation infrastructure for ML workloads.
  • Strong understanding of hardware/software co-design for inference acceleration.
  • Experience working with low-power edge platforms, NPUs, custom accelerators, GPUs, or closely related architectures.
  • Ability to reason about memory allocation, execution scheduling, bandwidth constraints, and overall system performance.
  • Experience translating research concepts into practical tooling and production workflows.
  • Exceptional cross-functional leadership skills and a history of driving impact through technical and strategic influence.
  • Preferred qualifications
  • Experience with quantization-aware training, post-training quantization, compression, pruning, and sparsity optimization.
  • Experience bringing vision or multimodal models from development through full deployment.
  • Familiarity with ONNX and model graph transformation pipelines.
  • Experience validating numerical behavior across float and integer execution paths.
  • Experience supporting external customers, partner enablement, or productization of AI platforms.
  • Background working with both model-level and hardware-level optimization problems.
  • Startup or founder-level experience building end-to-end AI platform capabilities.
  • Company Statements
  • 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 atcandidateaccommodations@rivian. com.

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 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.

How We Use AI in Our Hiring Process

To ensure transparency, we want candidates to know that Rivian uses i CIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role.

AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans.

We use AI to support efficiency and consistency, not to replace human judgment.

We are committed to a fair, thoughtful, and equitable experience for every candidate.

Participation in AI profile matching is entirely voluntary.

If you prefer that your profile not be used in this process, you can opt out at any time.

Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system.

Your current application remains active and will not be affected in any way.

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

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Sr. Manager, Hardware, Machine Learning/AI employer: Rivian

Rivian is an exceptional employer that fosters a dynamic and collaborative work culture, perfect for adventurous spirits who are passionate about electric vehicles and the outdoors. Employees benefit from comprehensive health insurance, paid time off, and opportunities for professional growth, all while contributing to a mission that prioritises sustainability and innovation. Located in Duncan, SC, this role offers the chance to work hands-on with cutting-edge technology in a supportive environment that values teamwork and personal development.

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Contact Details:

Rivian Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Sr. Manager, Hardware, Machine Learning/AI

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Rivian or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Rivian.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Rivian.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Rivian that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Sr. Manager, Hardware, Machine Learning/AI

Machine Learning Systems
Model Deployment
AI Infrastructure
Model Optimization
Quantization
Performance Tuning
Compiler Infrastructure

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Rivian.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Rivian and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Rivian

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Rivian uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.