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Senior Tesla Machine Learning Engineer Jobs in Riverton, NJ

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps ...

Machine Learning Engineer, Specialist

Malvern, PA · On-site

$112K - $134K/yr

We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines ...

Senior Engineer - Machine Learning

Ambler, PA · Hybrid

$100K - $138K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Senior Engineer - Machine Learning

Ambler, PA · On-site

$100K - $138K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

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Senior Tesla Machine Learning Engineer information

See Riverton, NJ salary details

$57K

$121.1K

$175.6K

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

As of Aug 27, 2026, the average yearly pay for senior tesla machine learning engineer in Riverton, NJ is $121,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $137,400.00 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.

What job categories do people searching Senior Tesla Machine Learning Engineer jobs in Riverton, NJ look for?

The top searched job categories for Senior Tesla Machine Learning Engineer jobs in Riverton, NJ are:

What cities near Riverton, NJ are hiring for Senior Tesla Machine Learning Engineer jobs?

Cities near Riverton, NJ with the most Senior Tesla Machine Learning Engineer job openings:

Infographic showing various Senior Tesla Machine Learning Engineer job openings in Riverton, NJ as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $121,141 per year, or $58.2 per hour.

Senior Machine Learning Engineer

BE Group

Malvern, PA • On-site

$120K - $158K/yr

Full-time

Posted 29 days ago


Job description

We are assisting our client in hiring for a Senior Machine Learning Engineer.
Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps financial institutions improve collections performance, deliver a better consumer experience, reduce operating costs, anticipate delinquencies, and make more informed credit decisions.

This is a hybrid position based in Malvern, Pennsylvania. Candidates should be local to the Greater Philadelphia region and able to work onsite several days a week.

As part of a significant investment in Data & AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role is focused on building the predictive intelligence that becomes part of the company's core SaaS platform.

This is a highly hands-on engineering opportunity for someone who enjoys solving real business problems with machine learning. You'll design, build, deploy, and continuously improve production models that help financial institutions better predict customer behavior, prioritize collections strategies, and improve lending outcomes.

Working alongside Product, Engineering, Data, and business leaders, you'll help transform large volumes of structured data into intelligent software capabilities that customers use every day. If you enjoy owning the entire machine learning lifecycle—from feature engineering and model development through deployment, monitoring, and optimization—this is an opportunity to make a measurable impact.

What We're Looking For
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
  • 3+ years of experience designing, developing, and deploying production machine learning solutions.
  • Strong Python and SQL development skills.
  • Experience building predictive models using structured data.
  • Experience with feature engineering, model evaluation, deployment, and ongoing model monitoring.
  • Experience working with cloud-based data platforms and modern machine learning frameworks.
  • Familiarity with Azure, Databricks, MLflow, MLOps, or similar technologies.
  • Experience collaborating with engineering, product, and business teams to deliver production-ready AI solutions.
Preferred Experience
  • Financial services, banking, lending, collections, credit risk, or fintech.
  • Building scalable data pipelines and production machine learning systems.
  • AI-assisted software development tools and modern engineering practices.
  • Passion for solving complex business problems through data and machine learning.