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Remote Tesla Machine Learning Engineer Jobs in Bellflower, CA

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams ... Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams ... Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

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All JobsTesla Machine Learning Engineer JobsRemote Tesla Machine Learning Engineer JobsRemote Tesla Machine Learning Engineer Jobs in Bellflower, CA

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 21, 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 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 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 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:

Remote Tesla Machine Learning Engineer jobs near you
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.

Staff Machine Learning Engineer

Prodege LLC

El Segundo, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, PTO

Posted 24 days ago

Job description

Job Description:
Read this part first:
This is a role for someone who wants to solve hard machine learning problems by building production systems that matter.
We're looking for a Staff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and the business to deliver measurable outcomes.
This is a deeply hands-on individual contributor role. You'll spend the majority of your time building, deploying, experimenting with, and improving production machine learning systems, not managing people or operating primarily at the architectural strategy level.
If you enjoy taking ownership of difficult ML problems, iterating quickly through experimentation, and seeing your work directly improve revenue, marketplace efficiency, and customer experience, this role is for you.
You'll build production ML systems for a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, powered by a data platform with 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics supporting both batch and real-time workflows.
Prodege:
A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.
As an organization, we go the extra mile to "Create Rewarding Moments" every day for our partners, consumers, and team. Come join us today!
What you'll own
  • Design, build, and operate production machine learning systems from development through deployment
  • Production models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization
  • Feature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement
  • Reliable production ML practices including testing, observability, retraining, and model health
  • Technical leadership through code reviews, collaboration, and mentoring less experienced engineers
  • Cross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems

What makes this role exciting
  • You'll work on machine learning problems that directly impact revenue, marketplace efficiency, and customer experience.
  • You'll own production systems-not just models-from experimentation through deployment and optimization.
  • You'll build on top of a production platform processing 50M daily events, 500M daily pipeline records, and a 100TB Iceberg lake.
  • You'll join a team with an active experimentation culture, shipping ML improvements that quickly reach production.
  • You'll have significant ownership while partnering with senior technical leaders to shape the future of ML at Prodege.
  • You'll work in an engineering culture embracing AI-assisted development to improve productivity and accelerate experimentation.

What you'll do
  • Design, build, deploy, and maintain production machine learning systems.
  • Develop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation.
  • Improve feature engineering, model performance, inference latency, and operational reliability.
  • Design and analyze offline evaluations and A/B experiments to validate business impact.
  • Partner with Data Engineering to build reliable data pipelines and feature sets for ML.
  • Contribute to MLOps practices including deployment, monitoring, retraining, and model lifecycle management.
  • Review code, mentor teammates, and help raise engineering quality across the ML organization.
  • Leverage AI-assisted development to accelerate research, prototyping, debugging, documentation, and experimentation.

What you'll bring (must-haves)
  • 6+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related technical fields.
  • 3+ years building, deploying, and operating production machine learning systems.
  • Strong experience building production recommendation, ranking, personalization, optimization, or prediction systems.
  • Experience working in AdTech, MarTech, Growth, Consumer Products, Marketplace platforms, or adjacent domains.
  • Strong understanding of:
    • Feature engineering
    • Offline and online inference
    • Experimentation and A/B testing
    • Model serving
    • Monitoring and retraining
    • MLOps best practices
  • Experience partnering closely with Product, Engineering, and Data teams to deliver measurable business outcomes.
  • Strong software engineering fundamentals with excellent coding skills.
  • Comfort operating in ambiguous environments while independently driving technical solutions.
  • Demonstrated ability to mentor engineers and influence technical decisions across teams.

Bonus points
  • Experience with ROAS optimization, bidding systems, rewards platforms, or monetization models.
  • Experience with streaming or near-real-time ML systems.
  • Experience with recommendation engines or personalization at scale.
  • Experience using feature stores or shared ML infrastructure.
  • Experience with causal inference, uplift modeling, or counterfactual reasoning.
  • Master's degree or PhD in Machine Learning, AI, Computer Science, or a quantitative discipline.
  • Experience using AI-assisted development tools in software engineering workflows.

Pay Transparency:
The anticipated base salary range for this position is $240,000 to $290,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Prodege Benefits:
Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.
Equal Employment Opportunity Statement
At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.
FCIHO
Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

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