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Remote Tesla Machine Learning Engineer Jobs (NOW HIRING)

Overview Machine Learning Engineer, AI Platform As a Machine Learning Engineer, you will design ... Work across multiple time zones in a hybrid or remote work environment. * Long periods of time ...

Overview Machine Learning Engineer, AI Platform As a Machine Learning Engineer, you will design ... Work across multiple time zones in a hybrid or remote work environment. * Long periods of time ...

Machine Learning Engineer

Seattle, WA · On-site +1

$164.70K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

Machine Learning Engineer

$121.60K - $160K/yr

A Machine Learning Engineer helps our learners discover content that is relevant to their interests ... This is a remote role; however, applicants located within 45 miles of our Westlake/Dallas, TX ...

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

New

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

Location- Remote Overview: As a GCP ML Engineer, you'll design, develop, and maintain machine learning pipelines and infrastructure on the Google Cloud Platform (GCP). You'll work closely with data ...

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

Machine Learning Engineer

Manhattan, NY · On-site +1

$170K - $212K/yr

Machine Learning Engineer The Music Promotion team is building products that allow creators to promote their work to reach new audiences and create lasting connections with their fans. We're looking ...

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

We are a remote-first company with a globally distributed team. You can find your productive zone and work from there. About The Role As a Machine Learning Engineer, you'll do more than build models ...

New

The Machine Learning Engineer will build and manage production machine learning systems, design data pipelines, and collaborate with engineers and product leaders to enhance decision-making processes ...

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Remote Tesla Machine Learning Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Jun 3, 2026, the average yearly pay for remote tesla machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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 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 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 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.

More about Remote Tesla Machine Learning Engineer jobs
What cities are hiring for Remote Tesla Machine Learning Engineer jobs? Cities with the most Remote Tesla Machine Learning Engineer job openings:
What are the most commonly searched types of Tesla Machine Learning Engineer jobs? The most popular types of Tesla Machine Learning Engineer jobs are:
What states have the most Remote Tesla Machine Learning Engineer jobs? States with the most job openings for Remote Tesla Machine Learning Engineer jobs include:
Infographic showing various Remote Tesla Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 82% Full Time, 13% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Kanak Elite Services Inc

Bodega Bay, CA • Remote

Contractor

Posted 18 days ago


Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Machine Learning Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Title:  Machine Learning Engineer
Location:  South San Francisco, CA  - hybrid role in Bay Arear
Position Type:  Contract 
 

Note: DO NOT SEND WITHOUT MOLECULAR EXPERIENCE, 

Work on ML workflows for molecular property prediction & generative modeling to accelerate drug discovery. 3–5 yrs esp. or PhD with publications in molecular design.

Must have Masters or PH.D. Must have experience in working environment or while getting Master’s or no to very little work exp with PH.D  in Molecular design. Need to have portfolio of their work or be published. Find me Machine Learning with Molecular experience in Bay Area or someone who will relocate as last resort. 
MindSource is looking for a Machine Learning Engineer to join our client's team in South San Francisco, CA.  They will be developing and deploying advanced computational methods for molecular design.  This is a 12-month hybrid contract.  

About the Role

  • Build pipelines for probabilistic molecular property prediction and Bayesian acquisition to power active learning–driven drug discovery.
  • Engineer workflows for molecular generative modeling and other innovative design approaches.
  • Collaborate with machine learning scientists, engineers, computational chemists, and biologists.
  • Partner with therapeutic development teams to analyze existing molecules and design new candidates.
  • Contribute to ongoing initiatives while driving new research directions.

Qualifications

  • PhD in Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics, or related quantitative field — OR MS + 3+ years of relevant industry experience.
  • Demonstrated expertise in production-ready ML workflows (e.g., PyTorch + Lightning + Weights & Biases).
  • Strong track record of achievement (e.g., high-impact first-author publication or equivalent).
  • Excellent written, visual, and verbal communication skills.

Preferred Experience

  • Knowledge of physical modeling (e.g., molecular dynamics) and cheminformatics (e.g., RDKit).
  • Background in molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, or statistical methods.
  • Hands-on experience with Python, PyTorch, Torch Geometric, PyTorch Lightning, RDKit, and BoTorch.
  • Public portfolio of computational projects (e.g., GitHub).