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Remote Tesla Machine Learning Engineer Jobs in Jackson, MS

Analytics Engineer (Remote)

Madison, MS ยท Remote

$115K - $208K/yr

Support machine learning and fraud modeling workflows, including feature engineering and model ... Flexible work environment, ability to work remote, hybrid or in-office. * Flexible time off ...

Develop and implement predictive models and machine learning algorithms. * Collaborate with cross ... Proficiency in programming languages such as Python or R. * Strong understanding of statistical ...

SDLC Engineer - AI Trainer

Jackson, MS ยท Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

QA Engineer - AI Trainer

Jackson, MS ยท Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

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Showing results 1-20

Remote Tesla Machine Learning Engineer information

See Jackson, MS salary details

$27.4K

$112.2K

$168.6K

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

As of Jun 24, 2026, the average yearly pay for remote tesla machine learning engineer in Jackson, MS is $112,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,400.00 and $135,100.00 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, and why are they important?

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 the most commonly searched types of Tesla Machine Learning Engineer jobs in Jackson, MS? The most popular types of Tesla Machine Learning Engineer jobs in Jackson, MS are:
What are popular job titles related to Remote Tesla Machine Learning Engineer jobs in Jackson, MS? For Remote Tesla Machine Learning Engineer jobs in Jackson, MS, the most frequently searched job titles are:
What job categories do people searching Remote Tesla Machine Learning Engineer jobs in Jackson, MS look for? The top searched job categories for Remote Tesla Machine Learning Engineer jobs in Jackson, MS are:
What cities near Jackson, MS are hiring for Remote Tesla Machine Learning Engineer jobs? Cities near Jackson, MS with the most Remote Tesla Machine Learning Engineer job openings:

Analytics Engineer (Remote)

Experian

Madison, MS โ€ข Remote

$115K - $208K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Job description

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

The Fraud Analytics & Commercialization team drives Experian\'s fraud analytics business through four integrated functions: pre-sales engagement, scalable and custom solutions, consulting, and operational enablement, with the goal of becoming the industry\'s provider-of-choice.

We\'re looking for an Analytics Engineer, Fraud Analytics Infrastructure, to join our Fraud Analytics team. As the ideal candidate, you thrive at the intersection of data engineering, infrastructure, and machine learning, and care about the reliability, scalability, and usability of the platforms your colleagues depend on. You\'ll work closely with data scientists, engineers, and product partners to build, maintain, and continuously improve the analytics ecosystem that enables fraud attribute development, model building, and model deployment, including identifying opportunities to increase efficiency and stability across the full modeling lifecycle. Core skills include navigating ambiguity, an impact-focused mindset, critical thinking, and an eagerness to collaborate across teams. You are curious about the latest tools and AI solutions, will evaluate their potential, and help bring the best of them into the team\'s workflows. Candidates who have taken an unconventional path and demonstrated the curiosity to figure things out without a blueprint will find this role and team to be a good fit.

You will report to the Data Modeling Director.

You\'ll have the opportunity to:

  • Build scalable Python-based data pipelines and backend services for analytics workflows.
  • Design software systems using object-oriented programming and sound engineering practices.
  • Create and support platforms that allow analytics development, model training, and model deployment.
  • Implement and maintain CI/CD pipelines and infrastructure-as-code solutions for automated deployments.
  • Manage cloud and on-premises analytics environments, including AWS infrastructure and security controls.
  • Monitor, troubleshoot, and improve data pipelines, platform performance, and system reliability.
  • Support machine learning and fraud modeling workflows, including feature engineering and model deployment.
  • Implement new technologies, including AI-based solutions, to improve platform efficiency and stability.
Qualifications
  • 3+ years of experience in data science, analytics, data engineering, or a related field.
  • Bachelor\'s or advanced degree in Statistics, Applied Mathematics, Econometrics, or another quantitative field; equivalent experience considered.
  • Experience developing applications and data pipelines using Python, including PySpark, Polars, NumPy, and Pandas.
  • Familiarity with Java and object-oriented programming concepts.
  • Experience building, deploying, and supporting production systems and data platforms.
  • Experience with AWS services such as EC2, EMR, and Airflow, including cloud security best practices.
  • Experience with machine learning workflows and analytics model development environments.
  • Experience with CI/CD processes, Infrastructure as Code, containerization tools, and UNIX/Linux environments.
Additional Information

Benefits/Perks:

  • Great compensation package and bonus plan.
  • Core benefits including medical, dental, vision, and matching 401K.
  • Flexible work environment, ability to work remote, hybrid or in-office.
  • Flexible time off including volunteer time off, vacation, sick and 12-paid holidays.
  • Explore all our exciting benefits here: https://myexperianbenefits.com/.

Our uniqueness is that we celebrate yours. Experian\'s people first, inclusive and purpose driven culture is multi award-winning; World\'s Best Workplacesโ„ข 2025 (Fortune Global Top 25), Great Place To Workโ„ข in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-Remote

This is a remote position.

  • Employee Status: Regular
  • Role Type: Hub
  • Job Posting - Salary Range: $115,747 - $208,344
  • Department: Analytics
  • Schedule: Full Time
  • Compensation: USD 115747 - USD 208344 - yearly