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Senior Tesla Machine Learning Engineer Jobs (NOW HIRING)

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As a Machine Learning Engineer, you will work with complex datasets, design and optimize models, and help bring intelligent solutions into production. You will collaborate with software engineers and ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

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$59.5K

$126.6K

$183.5K

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

As of Aug 7, 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.

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 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.

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.

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.
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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 August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Machine Learning Engineer

Aivra Health LLC

San Francisco, CA • On-site

Other

Medical, Retirement, PTO

Posted 22 days ago

Job description

Machine Learning Engineer

Location: San Francisco, CA, USA (Hybrid/Remote)

Job Type: Full-Time

About the Role

We are seeking an innovative Machine Learning Engineer to design, develop, and deploy machine learning models that solve real-world business challenges. You will collaborate with data scientists, software engineers, and product teams to build scalable AI-powered solutions.

Key Responsibilities
  • Design, train, and deploy machine learning models.
  • Build data preprocessing and feature engineering pipelines.
  • Optimize model performance and accuracy.
  • Deploy ML models into production environments.
  • Collaborate with Data Scientists and Software Engineers.
  • Monitor model performance and retrain models when needed.
  • Maintain documentation for ML workflows.
  • Research and implement new machine learning techniques.
Required Qualifications
  • Bachelor''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Strong Python programming skills.
  • Knowledge of Machine Learning algorithms.
  • Understanding of statistics and data structures.
  • Excellent analytical and problem-solving skills.
Preferred Skills
  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Pandas
  • NumPy
  • MLflow
  • AWS
  • Docker
  • Kubernetes
  • SQL
  • Git
Benefits
  • Health Insurance
  • Paid Time Off
  • Flexible Work Schedule
  • Learning & Development
  • 401(k)
  • Career Growth Opportunities

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