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Remote Mechanical Engineering Machine Learning Jobs in Texas

Electronic Arts

Machine Learning Engineer III

Austin, TX · On-site +1

$122K - $158K/yr

You will follow a hybrid work model with a mix of remote work and in-office collaboration. This ... Qualifications -Five or more years of professional experience in data engineering, machine learning ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

CVS Health

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

Feature engineering, model training, hyperparameter tuning, distributed model training, and supervised and unsupervised learning implementation; Quantitative analysis techniques, including clustering ...

New

CVS Health

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

Master's degree (or foreign equivalent) in Computer Science, Engineering, Machine Learning, Statistics, Mathematics, Analytics, Information Technology, or a related field and two (2) years of ...

New

Shipwell

Machine Learning Engineer

Austin, TX · On-site +1

Working closely with engineering, analytics, data science, and product teams, you'll take our machine learning capabilities to the next level. This is a dynamic opportunity to become the expert on ...

Varsity Tutors

Mechanical Engineering Tutor

Bryan, TX · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

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Remote Mechanical Engineering Machine Learning information

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms for automation, robotics, or predictive maintenance. Gaining skills in programming languages like Python, and understanding of machine learning frameworks, can facilitate their transition into this field.

What is the difference between Remote Mechanical Engineering Machine Learning vs Remote Mechanical Engineering?

AspectRemote Mechanical EngineeringRemote Mechanical Engineering Machine Learning
Required CredentialsBachelor's or Master's in Mechanical EngineeringBachelor's or Master's in Mechanical Engineering; knowledge of Machine Learning
Work EnvironmentDesign, analysis, CAD modeling, testingDesign, analysis, CAD modeling with ML integration, data analysis
Industry UsageManufacturing, automotive, aerospaceManufacturing, automotive, aerospace with AI/ML applications
Common Search/ComparisonYesYes

Remote Mechanical Engineering involves traditional engineering tasks like design and analysis, while Remote Mechanical Engineering Machine Learning combines these with AI techniques to optimize processes and develop intelligent systems. The latter requires additional knowledge of machine learning but shares many core skills and industry applications.

What is a Remote Mechanical Engineering Machine Learning job?

A Remote Mechanical Engineering Machine Learning job combines mechanical engineering expertise with machine learning techniques, allowing professionals to develop intelligent systems and optimize mechanical processes from a remote location. These roles often involve tasks such as analyzing engineering data, building predictive models, automating design tasks, and enhancing product performance using AI algorithms. Working remotely, engineers collaborate with teams through digital platforms, contributing to research, development, and deployment of machine learning solutions in mechanical engineering applications.

Can I work remotely as a machine learning engineer?

Yes, many machine learning engineers, including those in mechanical engineering applications, can work remotely. Remote work is common in tech roles that involve programming, data analysis, and model development, often requiring skills in Python, TensorFlow, or similar tools. However, some positions may require on-site collaboration or access to specialized equipment, depending on the company's policies and project needs.

Which 5 jobs will survive AI?

Remote Mechanical Engineering roles that involve complex problem-solving, design, and hands-on work are likely to persist despite AI advancements. Jobs requiring creativity, critical thinking, and specialized expertise—such as research engineers, systems designers, and technical consultants—are less susceptible to automation. Continuous learning and proficiency with engineering tools and software can also enhance job security in this field.

What are some typical challenges faced by remote mechanical engineers working with machine learning, and how can they be managed?

Remote mechanical engineers who work with machine learning often face challenges such as effective cross-functional collaboration, accessing and sharing large datasets, and keeping communication clear across distributed teams. To manage these, it's important to leverage collaborative tools for version control, data management, and regular virtual meetings. Building strong communication habits and proactively seeking feedback from data scientists, software engineers, and other stakeholders will help ensure project alignment and smooth workflows.

What engineers make $500,000?

Senior mechanical engineers with extensive experience, specialized skills in areas like automation or aerospace, and advanced certifications can reach or exceed a $500,000 annual salary, especially in high-demand industries or leadership roles. Achieving this level often requires years of expertise, advanced degrees, and working in high-paying sectors or companies.
What are the most commonly searched types of Mechanical Engineering Machine Learning jobs in Texas? The most popular types of Mechanical Engineering Machine Learning jobs in Texas are:
What are popular job titles related to Remote Mechanical Engineering Machine Learning jobs in Texas? For Remote Mechanical Engineering Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Remote Mechanical Engineering Machine Learning jobs in Texas look for? The top searched job categories for Remote Mechanical Engineering Machine Learning jobs in Texas are:
What cities in Texas are hiring for Remote Mechanical Engineering Machine Learning jobs? Cities in Texas with the most Remote Mechanical Engineering Machine Learning job openings:
Remote Mechanical Engineering Machine Learning jobs near you
Machine Learning Engineer III

Machine Learning Engineer III

Electronic Arts

Austin, TX • On-site, Remote

$122K - $158K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

Description & Requirements
Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.
Central Technology is the force multiplier, accelerating creative opportunity and progress at EA. We're a world-class community of technologists, innovators, strategists, and orchestrators transforming interactive entertainment. Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock bold new possibilities.
EA Security protects our players, employees, products, and platforms. We set security standards, support game and enterprise teams, assess risk across partners and systems, and ensure compliance with global requirements. Our work strengthens system integrity, supports fair play, and enables teams to build and operate securely at scale.
The Senior Machine Learning Engineer will report to the Senior Manager, EA Player Security Data Labs. You will follow a hybrid work model with a mix of remote work and in-office collaboration. This role focuses on building and operating production-grade data and machine learning infrastructure that enables data scientists and analysts to deliver fraud detection, anti-cheat, and account security solutions across EA games.
Responsibilities
-Design, build, and maintain scalable data ingestion, transformation, and feature pipelines that support machine learning workflows for fraud and anti-cheat systems.
-Own and operate production data and machine learning infrastructure, including batch and near-real-time data processing, feature generation, training workflows, and inference pipelines.
-Partner with data scientists to productionize machine learning models, with a strong focus on data consistency, data quality, and reliable offline and online feature computation.
-Ensure data and machine learning pipelines are reliable, repeatable, observable, and cloud agnostic across environments.
-Contribute to architectural standards, platform design decisions, and engineering best practices as a senior individual contributor within EA Player Security Data Labs.
Qualifications
-Five or more years of professional experience in data engineering, machine learning engineering, or a closely related role with production ownership.
-Strong proficiency in Python and SQL, with demonstrated experience building and maintaining large-scale, production-grade data pipelines. Rust Experience a Plus.
-Experience designing and operating data-intensive systems using modern programming languages, including Rust.
-Hands-on experience supporting end-to-end machine learning workflows, with an emphasis on data preparation, feature pipelines, and model deployment infrastructure.
-Experience working in cloud environments such as AWS or GCP, including large-scale data processing systems.
-Experience with containerization and orchestration technologies such as Docker and Kubernetes.
-Experience with CI/CD systems and production deployment workflows, including GitLab.
-Experience with Terraform and Spark
Why You Will Enjoy This Role
You will work on data and machine learning systems that protect millions of players from fraud and cheating.
You will operate as a senior individual contributor with strong technical ownership and autonomy.
You will design and build core data infrastructure that powers machine learning across EA Player Security.
Why We Are Excited About This Role
We build systems that directly protect player trust and fair play across EA games.
We value strong data engineering fundamentals and production-focused machine learning.
We support senior engineers with autonomy and opportunities to shape long-term technical direction.
Pay Transparency - North America
COMPENSATION AND BENEFITS
The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).
PAY RANGES
* British Columbia (depending on location e.g. Vancouver vs. Victoria) *$114,300 - $156,200 CAD
* Washington (depending on location e.g. Seattle vs. Spokane) *$122,300 - $158,500 USD
Pay is just one part of the overall compensation at EA.
In the US, we offer a package of benefits including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees. Certain roles may also be eligible for bonus and equity.
For Canada, we offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.
About Electronic Arts
We're proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.
We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.
Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.
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