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Remote Embedded Machine Learning Jobs in Texas (NOW HIRING)

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

... remote within a mutually acceptable location. #LI-Hybrid Success Looks Like: * AI systems move ... Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

Senior AI/ML Engineer - Hybrid

Irving, TX · On-site +1

$87K - $151K/yr

... of advanced machine learning and generative AI solutions. In this role, you will work at the ... The starting pay range for this remote role is $87,120-$151,250. This range reflects the minimum ...

Senior AI/ML Engineer - Hybrid

Irving, TX · On-site +1

$87K - $151K/yr

... of advanced machine learning and generative AI solutions. In this role, you will work at the ... The starting pay range for this remote role is $87,120-$151,250. This range reflects the minimum ...

Hands-on experience with adversarial machine learning techniques and tools (e.g., Foolbox ... Fully Remote: We are a completely remote global team. Though we're distributed, we are intentional ...

Data Scientist

Dallas, TX · On-site +1

$110K - $130K/yr

Role Overview We're seeking a Data Scientist with hands-on experience in machine learning ... Strong self-direction and communication skills suited for a remote work environment Nice to Have

Modeling Scientist

Houston, TX · On-site +1

$100K - $160K/yr

Remote Base Salary Range : $100k - $160k base salary The Modeling Scientist is responsible for ... Working at the intersection of statistics, machine learning, and process-based ecosystem modeling ...

... Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline Must have * Understanding of various machine learning algorithms (e.g. SVM, Random Forests ...

Develop and improve machine learning models for estimating crop biophysical * properties using satellite remote sensing datasets. * Implement spatial and remote sensing data processing algorithms to ...

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Showing results 1-20

Remote Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are the most commonly searched types of Embedded Machine Learning jobs in Texas? The most popular types of Embedded Machine Learning jobs in Texas are:
What are popular job titles related to Remote Embedded Machine Learning jobs in Texas? For Remote Embedded Machine Learning jobs in Texas, the most frequently searched job titles are:
What cities in Texas are hiring for Remote Embedded Machine Learning jobs? Cities in Texas with the most Remote Embedded Machine Learning job openings:
Staff Software Engineer, AI for Developer Productivity

Staff Software Engineer, AI for Developer Productivity

General Motors

Austin, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


General Motors rating

8.0

Company rating: 8.0 out of 10

Based on 309 frontline employees who took The Breakroom Quiz

6th of 44 rated automakers


Job description

Job Description

We are seeking a highly skilled Staff Software Engineer to join the Virtualization & Embedded Software Development Tools organization.

In this role, you will apply artificial intelligence to improve developer productivity, modernize engineering workflows, and advance toolchain capabilities across embedded software development. You will shape and deliver practical, production-grade AI capabilities that help engineers build, test, analyze, troubleshoot, and support complex software systems more effectively at scale.

This role is ideal for a recognized technical expert who thrives in ambiguity, works independently with broad latitude, influences key technical decisions, and leads large cross-functional efforts with broad visibility. You will partner across CI/CD, virtualization, systems engineering, calibration, platform, and software development teams to identify high-value opportunities and turn them into scalable solutions that improve engineering throughput, reliability, and user experience.

Our organization supports the end-to-end engineering toolchain that enables teams to define, develop, validate, calibrate, and release embedded software and systems. That includes engineering tools, build and test workflows, dashboards, automation, integrations, and engineering support platforms. As part of this team, you will help define how AI can be used responsibly and effectively in real engineering environments to improve speed, quality, and user experience.

What you'll do

  • Define the technical vision for AI-powered developer productivity capabilities across engineering tools and workflows
  • Design, develop, and deliver AI-powered solutions that reduce manual effort, accelerate issue resolution, and improve software quality across development, debugging, test analysis, issue triage, documentation, and engineering support workflows
  • Partner with cross-functional teams to identify high-value AI use cases and translate them into scalable products, platforms, and reusable capabilities
  • Integrate AI-powered capabilities into engineering tools, workflows, and automation platforms in ways that improve reliability, usability, and adoption
  • Lead architecture and implementation decisions for AI systems spanning model access, orchestration, retrieval, evaluation, observability, security, and enterprise integration
  • Drive productionization of AI capabilities within GM engineering environments, including cloud-hosted services, internal platforms, CI/CD systems, and developer tools
  • Establish technical standards and best practices for responsible use of AI in engineering tools, including quality, traceability, maintainability, and cybersecurity considerations
  • Serve as a subject matter expert and technical leader across organizational boundaries, influencing roadmaps, solution direction, and implementation priorities
  • Mentor engineers on AI system design, prompt and workflow design, evaluation strategies, and toolchain integration without formal people-leader responsibility
  • Present strategy, progress, recommendations, and demonstrations to technical leaders and partner organizations

Additional job description

Your skills and abilities (required qualifications)

  • Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical field
  • 10+ years of experience in software engineering, developer tooling, platform engineering, machine learning engineering, applied AI, or a closely related field
  • Strong expertise building and shipping production software systems, with proficiency in Python and at least one additional language used in engineering tooling environments
  • Demonstrated expertise applying AI and LLM-based approaches to engineering problems such as code analysis, workflow automation, knowledge retrieval, summarization, troubleshooting, or developer productivity support
  • Strong understanding of software engineering fundamentals, system design, APIs, data flows, observability, and production operations
  • Experience integrating AI-powered capabilities into enterprise platforms, engineering tools, or CI/CD systems
  • Experience with cloud services, containerization, and orchestration technologies
  • Strong knowledge of secure engineering practices and responsible AI guardrails
  • Demonstrated success leading technically ambiguous, cross-functional efforts from concept through production deployment
  • Excellent communication skills and the ability to influence technical direction across teams without formal authority
  • Experience with developer platforms, build systems, testing systems, or internal engineering tools
  • Experience balancing fast experimentation with production reliability, maintainability, and compliance

What can give you a competitive edge (preferred qualifications)

  • Master's degree or PhD in Computer Science, Software Engineering, Machine Learning, AI, or a related field
  • Experience in embedded software development, automotive software, systems engineering, or safety-related toolchains
  • Experience with CI/CD platforms, build and test orchestration, and software quality automation
  • Familiarity with GM engineering tools, engineering workflows, or internal platform environments
  • Experience building AI assistants, coding agents, or domain-specific AI capabilities for engineers
  • Experience with knowledge systems, vector search, ranking, workflow orchestration, or code intelligence platforms
  • Experience supporting large engineering communities through reusable tools, templates, and automation
  • Experience evaluating AI quality in production systems using measurable outcomes such as acceptance rate, time saved, precision and recall, hallucination reduction, or workflow completion rate
  • Experience designing retrieval-augmented or tool-using AI workflows
  • Experience integrating AI into GitHub-based engineering workflows or related enterprise automation pipelines

Why join us

This is an opportunity to shape how AI is applied in real-world engineering environments at scale. You will work on high-value problems at the intersection of developer productivity, toolchain modernization, automation, CI/CD, observability, and embedded software development. Your work will help engineering teams move faster, reduce friction, improve quality, and unlock new capabilities across a critical part of GM's software development ecosystem.

You will join a team that is actively modernizing and scaling core engineering toolchains, including CI/CD robustness, workflow automation, dashboarding and observability, configuration and calibration workflows, and platform evolution. This role offers the opportunity to turn promising AI concepts into reliable, enterprise-ready capabilities that deliver measurable value.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate.
The salary range for this role is ($160,200 - 246,300). The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits:
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

#LI-JK3

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.


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Pay

Benefits

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General Motors logo

About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908