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Tesla Machine Learning Engineer Jobs in Texas (NOW HIRING)

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98.10K - $129.20K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer II

Houston, TX · On-site

$93.10K - $127.50K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

Machine Learning Engineer II

Houston, TX · On-site

$93.10K - $127.50K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

Senior Machine Learning Engineer

Houston, TX

$117K - $154.20K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154.20K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Senior Machine Learning Engineer

Houston, TX

$117K - $154.20K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

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Tesla Machine Learning Engineer information

See Texas salary details

$29.3K

$120K

$180.3K

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

As of May 29, 2026, the average yearly pay for tesla machine learning engineer in Texas is $119,968.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,400.00 per year, depending on experience, location, and employer.

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 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 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.
What are the most commonly searched types of Tesla Machine Learning Engineer jobs in Texas? The most popular types of Tesla Machine Learning Engineer jobs in Texas are:
What cities in Texas are hiring for Tesla Machine Learning Engineer jobs? Cities in Texas with the most Tesla Machine Learning Engineer job openings:
Infographic showing various Tesla Machine Learning Engineer job openings in Texas as of May 2026, with employment types broken down into 93% Full Time, 6% Contract, and 1% Nights. Highlights an 10% Physical, 89% Hybrid, and 1% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Capital One

Plano, TX • On-site, Remote

$98.10K - $129.20K/yr

Full-time

Posted 12 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

74th of 141 rated banks


Job description

Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you'll do in the role:

  • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.

  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).

  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.

  • Retrain, maintain, and monitor models in production.

  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

  • Construct optimized data pipelines to feed ML models.

  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.

  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

  • Use programming languages like Python, Scala, or Java.


Basic Qualifications:

  • Bachelor's degree

  • At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)

  • At least 4 years of experience programming with Python, Scala, or Java

  • At least 2 years of experience building, scaling, and optimizing ML systems


Preferred Qualifications:

  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field

  • 3+ years of experience building production-ready data pipelines that feed ML models

  • 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

  • 2+ years of experience developing performant, resilient, and maintainable code

  • 2+ years of experience with data gathering and preparation for ML models

  • 2+ years of people leader experience

  • 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation

  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer


New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer


Plano, TX: $179,400 - $204,700 for Lead Machine Learning Engineer









Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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