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Remote Tesla Machine Learning Engineer Jobs in San Jose, CA

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs. Benefits ...

About the role We're looking for exceptional Machine Learning Engineers focused on Ads to help take Higgsfield's advertising platform to the next level. You'll work at the intersection of large-scale ...

Senior Machine Learning Engineer

Mountain View, CA ยท On-site +1

$230K - $265K/yr

As a Senior Machine Learning Engineer, you'll bring your strong software engineering mindset to ... The company is backed by early investors in Google, DeepMind, Zoom, and Tesla. Otter.ai is an equal ...

Senior Machine Learning Engineer At EvenUp, we leverage cutting-edge AI to bring fairness and accessibility to the legal system. Tackling the most complex legal document challenges requires expertise ...

Senior Machine Learning Engineer

Mountain View, CA ยท On-site +1

$123K - $169K/yr

We're looking for a Senior Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-game ...

Showing results 41-60

Remote Tesla Machine Learning Engineer information

See San Jose, CA salary details

$36.9K

$150.9K

$226.8K

How much do remote tesla machine learning engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for remote tesla machine learning engineer in San Jose, CA is $150,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,000.00 and $181,700.00 per year, depending on experience, location, and employer.

What does a remote Tesla machine learning engineer do?

A Remote Tesla Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models to improve Tesla's products and services. Working from a remote location, they collaborate with teams to analyze large datasets, build predictive models, and optimize algorithms for applications such as autonomous driving, energy management, and manufacturing. They also ensure that machine learning solutions are scalable and meet Tesla's high standards for performance and safety.

What are the key skills and qualifications needed to thrive as a remote Tesla machine learning engineer?

To thrive as a Remote Tesla Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning principles, typically demonstrated through a relevant degree or equivalent experience. Proficiency with Python, TensorFlow or PyTorch, cloud platforms, and version control systems is crucial, and certifications in AI/ML can be advantageous. Exceptional problem-solving, communication, and self-motivation are important soft skills for collaborating remotely and tackling complex projects. These skills enable engineers to design, implement, and scale innovative AI solutions that drive Tesla's technology forward.

What are some common challenges faced by remote Tesla machine learning engineers, and how can they be overcome?

Remote Tesla Machine Learning Engineers often face challenges such as collaborating across different time zones, ensuring effective communication with cross-functional teams, and maintaining access to high-performance computing resources. To overcome these, engineers typically use collaborative tools for code sharing and project management, participate in regular virtual meetings, and leverage Tesla's robust cloud infrastructure for experimentation and model training. Proactively seeking feedback and staying aligned with team goals are also key practices for success in this remote, fast-paced environment.

What is the difference between Remote Tesla Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Tesla Machine Learning EngineerRemote Data Scientist
Required CredentialsDegree in Computer Science, Engineering, or related field; experience with ML frameworksDegree in Statistics, Mathematics, or related field; strong programming skills
Work EnvironmentCollaborates with engineering teams on autonomous systems and vehicle dataAnalyzes large datasets to extract insights for business or product decisions
Employer & Industry UsagePrimarily in automotive, tech, and autonomous vehicle sectorsAcross tech, finance, healthcare, and various industries

While both roles involve data analysis and machine learning, the Remote Tesla Machine Learning Engineer focuses on developing algorithms for autonomous vehicles, whereas the Remote Data Scientist analyzes data to inform business strategies. The roles share similar credentials but differ in application and industry focus.

What are the most commonly searched types of Tesla Machine Learning Engineer jobs in San Jose, CA?

The most popular types of Tesla Machine Learning Engineer jobs in San Jose, CA are:

What job categories do people searching Remote Tesla Machine Learning Engineer jobs in San Jose, CA look for?

The top searched job categories for Remote Tesla Machine Learning Engineer jobs in San Jose, CA are:

What cities near San Jose, CA are hiring for Remote Tesla Machine Learning Engineer jobs?

Cities near San Jose, CA with the most Remote Tesla Machine Learning Engineer job openings:

Infographic showing various Remote Tesla Machine Learning Engineer job openings in San Jose, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $150,916 per year, or $72.6 per hour.

Staff Machine Learning Engineer

EvenUp

San Francisco, CA โ€ข Remote

$212K - $301K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Job description

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more.

We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com.

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how machine learning powers Piai™, our proprietary claims-intelligence platform. This is a technical leadership role - you'll shape modeling strategy across a broad problem space, turning raw legal and medical data into production systems that improve outcomes for personal-injury clients.

You'll partner closely with Product, Research, and Engineering leaders to set strategy, and you'll be a technical anchor for the broader ML team - setting standards, mentoring senior engineers, and driving decisions that shape both product outcomes and company growth.

What You'll Do
  • Set technical strategy for a broad area of the ML roadmap, translating ambiguous business and research goals into scoped, production-ready systems.

  • Tackle the hardest modeling problems in the org - complex reasoning, long-context and multi-document understanding, or other frontier challenges as they come up.

  • Apply advanced ML techniques - fine-tuning, reinforcement learning, retrieval, or others - and know when a technique is the right tool versus over-engineering.

  • Establish rigorous evaluation standards, reducing hallucinations, improving factual consistency, and defining what "good" looks like for a given system.

  • Drive data excellence through hands-on analysis of training and evaluation data, managing noise, edge cases, and drift at scale.

  • Provide technical leadership and mentorship across the ML team, raising the bar for experimentation, benchmarking, and engineering rigor.

  • Act as the bridge between research and production - ensuring new techniques get integrated into shippable systems, not just proofs of concept.

  • Partner cross-functionally with product, engineering, and legal subject-matter experts to set technical direction.

  • Cost effectively scale practical machine learning systems in a hyper-growth environment, ensuring they remain grounded in real business and customer needs.

What You Bring
  • 7+ years of hands-on ML engineering experience, with multiple models shipped and running in production.

  • Deep expertise in ML and NLP, including LLMs, with a track record of solving hard modeling problems - not just applying existing recipes.

  • High proficiency in Python and strong command of modern ML/NLP frameworks.

  • Demonstrated ability to set technical strategy and drive execution in ambiguous, fast-moving environments.

  • A track record of mentoring engineers and raising technical standards beyond your own output.

  • Experience partnering directly with Product and Engineering leadership, not just executing their asks.

Nice to Have
  • PhD in Machine Learning, Computer Science, or a related quantitative field.

  • Experience with document understanding, entity/relationship extraction, or structured extraction from unstructured text.

  • Experience with LLM fine-tuning techniques (LoRA, QLoRA, RLHF/RLVR) or advanced prompt engineering.

  • Experience in a high-growth startup environment.

  • Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs.

Benefits & Perks:

As part of our total rewards package, we offer attractive benefits and perks to our employees, including:

  • Choice of medical, dental, and vision insurance plans for you and your family.

  • Additional insurance coverage options for life, accident, or critical illness.

  • Flexible paid time off, sick leave, short-term and long-term disability.

  • 10 US observed holidays, and Canadian statutory holidays by province.

  • A home office stipend.

  • 401(k) for US-based employees and RRSP for Canada-based employees.

  • Paid parental leave.

  • A local in-person meet-up program.

  • Hubs in San Francisco and Toronto.

(Please note the above benefits & perks are for full-time employees)

Notice to Candidates:

To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you’re interested in a role, please submit your application directly through our careers page.

Please note that EvenUp may use AI notetakers and other recording devices in the recruiting process. If you interview with us, with your consent, we may record your conversations and summarize them into notes for internal use. Recording is optional, and declining will not affect your candidacy.

EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Compensation Range: $212K - $301K