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Senior Tesla Machine Learning Engineer Jobs in Santa Rosa, CA

Scientific Data Engineer

Bodega Bay, CA

$135K - $163K/yr

Support machine learning and AI use of biological data by making it well-structured, documented ... Network with senior internal and external personnel in their own area of expertise. We are looking ...

Showing results 21-40

Senior Tesla Machine Learning Engineer information

See Santa Rosa, CA salary details

$65.1K

$138.4K

$200.6K

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

As of Sep 4, 2026, the average yearly pay for senior tesla machine learning engineer in Santa Rosa, CA is $138,369.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,300.00 and $156,900.00 per year, depending on experience, location, and employer.

What does a senior Tesla machine learning engineer do?

A Senior Tesla Machine Learning Engineer leads the development and deployment of advanced machine learning models to improve Tesla’s products, such as Autopilot, Full Self-Driving, and manufacturing optimization. They collaborate with multidisciplinary teams to collect data, design algorithms, and ensure models are robust and scalable. In this role, engineers are expected to mentor junior staff, drive research initiatives, and help translate cutting-edge AI advancements into real-world Tesla applications.

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

To thrive as a Senior Tesla Machine Learning Engineer, you need deep expertise in machine learning algorithms, strong programming skills in Python or C++, and a proven track record in deploying models at scale, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience working with large datasets, and cloud computing platforms are typically required, as well as knowledge of Tesla's proprietary systems. Exceptional problem-solving, collaboration, and communication skills distinguish top performers in this role. These abilities are crucial for developing advanced AI solutions that power Tesla's autonomous systems and for driving innovation in a highly competitive, fast-evolving environment.

How does a senior Tesla machine learning engineer typically collaborate with cross-functional teams?

As a Senior Machine Learning Engineer at Tesla, you will frequently work alongside software developers, data scientists, product managers, and hardware engineers. Collaboration is highly cross-functional, with regular meetings to align on project goals, data requirements, and model deployment strategies. You may be involved in translating business objectives into machine learning solutions, sharing insights with non-technical stakeholders, and refining algorithms based on feedback from various departments. This collaborative environment fosters innovation and ensures that machine learning models are well-integrated into Tesla's products and systems.

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

AspectSenior Tesla Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models for autonomous vehicles, energy, and manufacturingAnalyzes data to extract insights, supports product and business decisions
Employer & Industry UsageTesla, automotive, energy, AI projectsVarious industries including tech, finance, healthcare

While both roles involve working with data and algorithms, the Senior Tesla Machine Learning Engineer focuses on developing and deploying machine learning models for Tesla's products, especially autonomous systems. In contrast, a Data Scientist primarily analyzes data to inform business decisions across various industries. The ML Engineer role requires deeper expertise in machine learning frameworks and deployment, whereas Data Scientists focus more on statistical analysis and data visualization.

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The top searched job categories for Senior Tesla Machine Learning Engineer jobs in Santa Rosa, CA are:

What cities near Santa Rosa, CA are hiring for Senior Tesla Machine Learning Engineer jobs?

Cities near Santa Rosa, CA with the most Senior Tesla Machine Learning Engineer job openings:

Software Engineering Lead, Machine Learning

Ema

Bodega Bay, CA • On-site

$200K - $270K/yr

Full-time

Re-posted 11 days ago


Job description

About Ema

Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.

We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale.

Who you are

We're looking for an innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related Machine Learning technologies. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact.

You will:
  1. Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems.

  2. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems.

  3. Lead the processing and analysis of large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inform the development of our models.

  4. Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.

  5. Implement A/B testing and other statistical methods to validate the effectiveness of models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.

  6. Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption.

Ideally, you'd have:
  1. A Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.

  2. Proven industry experience in building and deploying production-level machine learning models.

  3. Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models.

  4. Deep understanding of any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build them for large systems.

  5. Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch.

  6. Excellent skills in data processing (SQL, ETL, data warehousing) and experience working with large-scale data systems.

  7. Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices.

  8. Familiarity with cloud platforms like GCP or Azure.

  9. Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects.

  10. Good understanding of software development principles, data structures, and algorithms.

  11. Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking.

  12. The ability to work collaboratively in an extremely fast-paced, startup environment.

For California based candidates:
The standard base salary for this position is $200,000-$270,000 annually.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.