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Tesla Machine Learning Engineer Jobs in Houston, TX

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

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Tesla Machine Learning Engineer information

See Houston, TX salary details

$30.1K

$123K

$184.8K

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

As of Jun 15, 2026, the average yearly pay for tesla machine learning engineer in Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Tesla Machine Learning Engineer position, and why are they important?

To thrive as a Tesla Machine Learning Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree and practical experience with AI models. Proficiency with programming languages like Python or C++, deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud-based computing platforms are typically required. Strong problem-solving abilities, collaboration, and effective communication set top candidates apart in a team-oriented, innovative environment. These skills and qualities are crucial for developing robust AI solutions that drive Tesla's cutting-edge technologies and support its mission of advancing sustainable transport.

What is a Tesla Machine Learning Engineer job?

A Tesla Machine Learning Engineer develops and optimizes AI models for applications such as autonomous driving, manufacturing automation, and energy management. They work with large datasets, train deep learning models, and deploy solutions to improve Tesla’s technologies. The role involves collaboration with software engineers, data scientists, and hardware teams to enhance performance and efficiency. Strong programming skills, proficiency in frameworks like TensorFlow or PyTorch, and experience with real-world machine learning deployment are essential.

What are the most common challenges faced by Tesla Machine Learning Engineers, and how are they addressed?

Tesla Machine Learning Engineers often tackle challenges such as processing large-scale data sets, optimizing models for real-time performance, and accommodating frequent changes in project requirements. These challenges are addressed by leveraging Tesla’s high-performance computing resources, working closely with cross-functional teams—including hardware, software, and data engineering—and continuously iterating on solutions. The collaborative culture at Tesla encourages knowledge sharing and innovative problem-solving, helping engineers adapt quickly. If you're motivated by complex challenges and rapid innovation, you'll find opportunities to learn and grow while making direct impacts on disruptive products.

Infographic showing various Tesla Machine Learning Engineer job openings in Houston, TX as of June 2026, with employment types broken down into 95% Full Time, 4% Part Time, and 1% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $122,971 per year, or $59.1 per hour.
Machine Learning Engineer, Data & Insights, Surface & HSE

Machine Learning Engineer, Data & Insights, Surface & HSE

Chevron

Houston, TX • On-site

$109K - $131K/yr

Full-time

Posted 14 days ago


Chevron rating

6.0

Company rating: 6.0 out of 10

Based on 213 frontline employees who took The Breakroom Quiz

57th of 74 rated oil and gas companies


Job description

Total Number of Openings
1
Chevron is accepting online applications for the position Machine Learning Engineer, Data & Insights, Surface & HSE through June15th, 2025 at 11:59 p.m. (CST)
Overview
Chevron is seeking a Machine Learning Engineer to transform AI and data science concepts into scalable, production-grade solutions. You will build, deploy, and maintain machine learning systems that operate reliably at enterprise scale. Working alongside data scientists, software engineers, and cross-functional partners, you will bridge the gap between research and production to deliver AI systems aligned with strategic business objectives. Your work will drive smarter decisions and measurable outcomes across the organization, with strong emphasis on enterprise data platforms, AI-enabled transformation, and real-time analytics in complex domains such as Upstream (Surface) and Health Safety and Environment (HSE).
Responsibilities for this position may include but are not limited to:
Solution Design & Development
Identify data sources, technology stacks, and design patterns to address business challenges using AI and ML, with emphasis on Azure-based data platforms and enterprise architectures.
Partner with Data Scientists, Data Engineers, and IT teams to integrate models into enterprise data pipelines and large-scale data ecosystems.
Design scalable data and AI solutions enabling near real-time analytics and cross-domain data integration.
Model Operationalization
Transform prototypes into scalable, production-ready solutions across distributed and cloud-native environments.
Design and execute experiments to fine-tune algorithms for performance, latency, and resource efficiency, aligned with enterprise-scale workloads.
Configure and manage infrastructure for low-latency, highly available, and resilient ML workloads integrated with enterprise data platforms.
Deployment & Integration
Build, maintain, and optimize CI/CD pipelines for automated AI/ML deployments using modern DevOps and automation tooling.
Integrate models with enterprise MLOps infrastructure, APIs, and downstream business applications across multiple domains.
Leverage automation tools to operationalize workflows and improve delivery consistency.
Monitoring & Maintenance
Implement comprehensive monitoring, alerting, and exception-handling systems for deployed models and data pipelines.
Collaborate with Data Scientists and business stakeholders to ensure inference outputs drive accurate, consistent, and high-value decisions.
Proactively identify and resolve model drift, performance degradation, data quality issues, and system integration challenges.
Required Qualifications
- Bachelor's degree in Engineering, Computer Science, Data Science, or a related technical field.
- Minimum 7 years of hands-on experience in software engineering, ML engineering, or enterprise data platforms, with strong proficiency in Python.
- Proven track record of deploying machine learning models and/or enterprise data-driven platforms into production environments at scale.
- Solid understanding of the AI/ML lifecycle, including data preparation, model training, evaluation, deployment, and inference.
- Experience with Azure cloud services, including Azure Machine Learning, data platforms, and enterprise integration patterns.
- Experience building and maintaining CI/CD pipelines and applying DevOps practices for ML systems.
- Strong understanding of data governance principles (e.g., Lineage, MDM) and integration across enterprise systems.
- Demonstrated ability to troubleshoot complex distributed systems and work across cross-functional teams.
Preferred Qualifications
- Master's or Ph.D. in Engineering, Computer Science, Data Science, or a related field.
- 10+ years of relevant technical and enterprise experience in AI, data platforms, or digital transformation.
- Experience with large-scale enterprise data architectures and real-time analytics platforms.
- Deep understanding of model lifecycle management, performance optimization, and ML system design patterns in enterprise environments.
- Domain experience in Oil & Gas, including Surface, Subsurface, Wells and HSE
- Experience enabling AI adoption, defining enterprise roadmaps, and delivering measurable business value through data and AI solutions.
Relocation Options:
Relocation is not offered for this role. Only local candidates will be considered.
International Considerations:
Expatriate assignments will not be considered.
Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position.
U.S. Regulatory notice:
Chevron is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin or ancestry, age, mental or physical disability, medical condition, reproductive health decision-making, military or veteran status, political preference, marital status, citizenship, genetic information or other characteristics protected by applicable law.
U.S. Regulatory notice:
Chevron is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin or ancestry, age, mental or physical disability, medical condition, reproductive health decision-making, military or veteran status, political preference, marital status, citizenship, genetic information or other characteristics protected by applicable law.
We are committed to providing reasonable accommodations for qualified individuals with disabilities. If you need assistance or an accommodation, please email us at emplymnt@chevron.com.
Chevron participates in E-Verify in certain locations as required by law.

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About Chevron

Sourced by ZipRecruiter

Chevron is one of the world's leading integrated energy companies. We believe affordable, reliable and ever-cleaner energy is essential to achieving a more prosperous and sustainable world. Chevron produces crude oil and natural gas; manufactures transportation fuels, lubricants, petrochemicals and additives; and develops technologies that enhance our business and the industry. We are focused on lowering the carbon intensity in our operations and seeking to grow lower carbon businesses along with our traditional business lines. More information about Chevron is available at www.chevron.com.

Industry

Oil and coal products manufacturing, civic and social organizations and oil and gas extraction

Company size

10,000+ Employees

Headquarters location

San Ramon, CA, US

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