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Remote Tesla Machine Learning Engineer Jobs in Bellflower, CA

This individual will be focused on designing, building, and deploying machine learning models and ... Working closely with product managers, engineering teams, and business stakeholders, this position ...

You will collaborate closely with other Data Engineers, Machine Learning Engineers, Scientists, and business analysts to build scalable access patterns for them.Who you are: * You would consider ...

This is a remote position. * Develop both front and back-end components. * Collaborate with teams ... Use data-driven approaches to train and improve machine learning models for automation tasks.

Data foundations that support machine learning, feature pipelines, experimentation, and decisioning * Hands-on technical leadership across the Data Engineering organization through direct ...

This individual has expertise in machine learning, statistical modeling, and data visualization to ... This is a remote position. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Design, build, train, and ...

Senior Platform Engineer

Los Angeles, CA · On-site +1

$112K - $154K/yr

... remote work days. The Role EDO is looking for a Senior Platform Engineer to help accelerate our ... machine learning engineers ship safely and efficiently. Our environment is AWS-heavy and data ...

... machine learning to help predict and improve audience response to creative work across TV, film ... not a dogmatic engineer. ● Entertainment industry background is not required. ● Must be ...

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Showing results 41-60

Remote Tesla Machine Learning Engineer information

See Bellflower, CA salary details

$32.9K

$134.6K

$202.2K

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

As of Aug 16, 2026, the average yearly pay for remote tesla machine learning engineer in Bellflower, CA is $134,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $162,000.00 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 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 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 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 popular job titles related to Remote Tesla Machine Learning Engineer jobs in Bellflower, CA?

For Remote Tesla Machine Learning Engineer jobs in Bellflower, CA, the most frequently searched job titles are:

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

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

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

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

Infographic showing various Remote Tesla Machine Learning Engineer job openings in Bellflower, 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 $134,560 per year, or $64.7 per hour.

Data Scientist II

CorVel Healthcare Corporation

Irvine, CA • On-site, Remote

Full-time

Re-posted 9 days ago


Job description

We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production ready solutions by translating complex business problems into data-driven approaches and model-based outputs.

Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real world use cases. The role includes hands on model development, feature engineering, and integration into production systems within cloud environments.

The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred.

Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting.

This position is open to remote or hybrid.

ESSENTIAL FUNCTIONS & RESPONSIBILITIES:

  • Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies
  • Creating new, experimental frameworks to collect data
  • Building tools to automate data collection
  • Develop custom data models and algorithms to apply to data sets
  • Design, build, train, and deploy machine learning models and data products for enterprise use
  • Translate business and operational needs into scalable data science solutions and modeling approaches
  • Perform feature engineering, data preparation, and exploratory analysis to support model development
  • Develop and evaluate models using appropriate techniques (e.g., classification, regression, NLP, optimization)
  • Contribute to the design of data products, including model outputs, APIs, and integration into downstream systems
  • Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate
  • Collaborate with engineering teams to integrate models into production environments using APIs, pipelines, and cloud services
  • Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or similar platforms
  • Perform model validation, testing, and documentation to ensure quality and reproducibility
  • Contribute to technical design discussions and provide input on architecture and implementation strategies
  • Work within the full software development lifecycle (SDLC), including version control, testing, and release processes
  • Communicate model behavior, assumptions, and results clearly to technical and non-technical stakeholders
  • Develop A/B testing framework and test model quality
  • Passion for technology and emerging AI/ML trends
  • Additional duties as assigned

KNOWLEDGE & SKILLS:

  • Strong problem-solving skills with an emphasis on product development.
  • Strong foundation in machine learning, statistical modeling, and data science techniques
  • Experience building and deploying machine learning models in production environments
  • Familiarity with modern AI approaches, including:
    • Natural language processing (NLP)
    • Large language models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Feature engineering and model evaluation techniques
  • Experience working with cloud platforms such as Azure, AWS, or similar ecosystems
  • Familiarity with data pipelines, APIs, and integration patterns
  • Proficiency in programming languages such as Python and database management including SQL
  • Strong problem-solving skills with the ability to structure complex problems into analytical solutions
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications
  • Excellent presentation and written/verbal communication skills

EDUCATION & EXPERIENCE:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master’s preferred
  • 2–5+ years of experience in data science, machine learning, or related roles
  • Experience developing and deploying machine learning models in production environments
  • Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar
  • Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred
  • Experience working within enterprise software environments and SDLC practices preferred

PAY RANGE:

CorVel uses a market based approach to pay and our salary ranges may vary depending on your location. Pay rates are established taking into account the following factors: federal, state, and local minimum wage requirements, the geographic location differential, job-related skills, experience, qualifications, internal employee equity, and market conditions. Our ranges may be modified at any time.

For leveled roles (I, II, III, Senior, Lead, etc.) new hires may be slotted into a different level, either up or down, based on assessment during interview process taking into consideration experience, qualifications, and overall fit for the role. The level may impact the salary range and these adjustments would be clarified during the offer process.

Pay Range: $82,574 – $127,490

A list of our benefit offerings can be found on our CorVel website: CorVel Careers | Opportunities in Risk Management

In general, our opportunities will be posted for up to 1 year from date of posting, or until we have selected candidate(s) to fulfill the opening, whichever comes first.

About CorVel

CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers’ compensation, auto, health and disability management industries. CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients. We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities. Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

A comprehensive benefits package is available for full-time regular employees and includes Medical (HDHP) w/Pharmacy, Dental, Vision, Long Term Disability, Health Savings Account, Flexible Spending Account Options, Life Insurance, Accident Insurance, Critical Illness Insurance, Pre-paid Legal Insurance, Parking and Transit FSA accounts, 401K, ROTH 401K, and paid time off.

CorVel is an Equal Opportunity Employer, drug free workplace, and complies with ADA regulations as applicable.

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