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Senior Tesla Machine Learning Engineer Jobs (NOW HIRING)

Tesla

Machine Learning Engineer, Digital Optimus

Palo Alto, CA · On-site

$122.40K - $151.20K/yr

Tesla is seeking a Machine Learning Engineer for their Digital Optimus project. The role involves building and improving training, inference, data, and evaluation systems for advanced computer-use ...

New

Tesla

Machine Learning Engineer, Digital Optimus

Palo Alto, CA · On-site

$122.40K - $151.20K/yr

Tesla is seeking a Machine Learning Engineer for their Digital Optimus project, where the role involves building training and evaluation systems for advanced computer-use agents. The engineer will ...

New

k1x

Machine Learning Engineer

Manhattan, NY · Remote

As a Machine Learning Engineer, you will play a critical role in developing and implementing ... results to senior leaders and nontechnical audiences Proficiency in Python and a strong ...

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Senior Tesla Machine Learning Engineer information

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$59.5K

$126.6K

$183.5K

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

As of Jun 3, 2026, the average yearly pay for senior tesla machine learning engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Tesla Machine Learning Engineer, and why are they important?

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 Machine Learning Engineer at Tesla 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 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 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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What cities are hiring for Senior Tesla Machine Learning Engineer jobs? Cities with the most Senior Tesla Machine Learning Engineer job openings:
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Senior Tesla Machine Learning Engineer jobs near you
Infographic showing various Senior Tesla Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.
Sr. Software & Machine Learning Engineer, Energy Optimization

Sr. Software & Machine Learning Engineer, Energy Optimization

Tesla

Palo Alto, CA • On-site

$144.20K - $190.10K/yr

Full-time

Posted 27 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is committed to accelerating the world’s transition to sustainable energy, and they are seeking a Sr. Software & Machine Learning Engineer to develop and maintain software systems that enhance their residential energy solutions. This role involves creating scalable machine learning models for energy storage forecasting and collaborating with cross-functional teams to integrate these systems into Tesla’s ecosystem.
Responsibilities:
• Develop and maintain scalable machine learning models and algorithms for energy storage forecasting, demand modeling, and system optimization, including demand response and grid integration
• Design and implement new features to enhance customer-facing applications and improve user experience
• Optimize deployment processes through CI/CD, containerization, and infrastructure management, ensuring smooth operations and efficient updates
• Collaborate with cross-functional teams to integrate software systems into Tesla’s ecosystem, ensuring seamless deployment and operation
• Build and maintain robust software pipelines for training, evaluating, and deploying ML models in production, ensuring reliability and efficiency
• Contribute to the development and maintenance of monitoring and simulation systems to ensure software reliability and scalability
• Proactively identify and resolve performance bottlenecks related to infrastructure, memory, and runtime efficiency
• Communicate technical concepts clearly to non-technical stakeholders to align development with business objectives
Qualifications:
Required:
• Degree in Computer Science, Engineering, or equivalent experience
• Strong proficiency in Python and Linux environments; experience with Go or Rust is a plus
• Proven experience in developing and deploying scalable software systems, including writing production-level code and ensuring performance in real-world environments
• Experience with cloud and big data technologies such as AWS, Spark, Airflow, and Kubernetes
• Experience with CI/CD pipelines (e.g., GitHub Actions) and automating software deployment processes
• Familiarity with optimization techniques, machine learning, and time-series forecasting is highly valued
• Excellent communication skills and the ability to collaborate within cross-functional teams
• Experience in energy solutions, battery control systems, and a passion for sustainability and clean energy solutions
Preferred:
• Practical experience in optimization techniques, time-series forecasting, and machine learning model development, with a focus on energy storage and grid applications is a plus
• Experience managing containerized applications in embedded or firmware environments, and optimizing resource usage (e.g., memory, CPU) for efficient performance in constrained systems is a plus
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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