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Remote Embedded Machine Learning Jobs in Texas (NOW HIRING)

Sr Machine Learning Engineer

Irving, TX · On-site +1

$112K - $185K/yr

Remote work permitted but must live within commuting distance of designated office location and ... Machine learning algorithms; Feature engineering, model training, hyperparameter tuning ...

New

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... The Opportunity The Senior Artificial Intelligence and Machine Learning Engineer will be part of a ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

Embedded AI Engineer - Finance

Dallas, TX · On-site +1

$130K - $171K/yr

Virtual (Remote) Position Type: PW Who We Are Gigapower is building next-generation fiber broadband ... Explains technical concepts clearly and drives adoption across stakeholder groups. • Learning ...

Virtual (Remote) Position Type: PW Who We Are Gigapower is building next-generation fiber broadband ... learning technology operations, network infrastructure, and business processes. Preferred ...

Embedded AI Engineer - Engineering

Dallas, TX · On-site +1

$130K - $171K/yr

Virtual (Remote) Position Type: PW Who We Are Gigapower is building next-generation fiber broadband ... for learning new technologies and understanding complex business operations. Preferred ...

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

REMOTE Anticipated Start Date: 07/01/2026 The US base salary range for this full-time position is ... Lead the development and deployment of advanced machine learning models to forecast outcomes and ...

Showing results 21-40

Remote Embedded Machine Learning information

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 are the key skills and qualifications needed to thrive as a remote embedded machine learning engineer?

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 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 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 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:

Director, Machine Learning - Search & Recommendation

Upwork

Austin, TX • Remote

Full-time

Medical, Retirement, PTO

Re-posted yesterday


Job description

Upwork Inc.'s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond.

Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn, Facebook, Instagram, TikTok, and X; and learn more about Lifted at Go-Lifted and follow on LinkedIn.


Search & Recommendations sits at the center of how work happens on Upwork. In this role, you will lead the engineering organization responsible for building the systems that connect millions of clients and freelancers across the globe. You will shape the future of Upwork's matching platform by setting technical direction, scaling core systems, and delivering experiences that power everything from search and browse to conversational matching, agentic workflows, and emerging AI-native surfaces. This is a high-impact leadership opportunity to guide a strong engineering team while partnering closely with product, machine learning, and executive leadership on a platform central to Upwork's long-term growth.

Responsibilities
  • Define and drive the technical strategy for Upwork's Search & Recommendations platform, aligning engineering investments with long-term business goals, marketplace performance, and platform scalability.
  • Lead, grow, and develop a high-performing organization of software and machine learning engineers, fostering a culture of ownership, inclusion, high standards, and continuous learning.
  • Deliver a unified Search & Recommendations platform that powers matching experiences across client and talent journeys, including search, recommendations, conversational experiences, and agentic workflows.
  • Modernize search infrastructure by guiding the migration from legacy systems to scalable, maintainable, and high-performance architectures with clear APIs, observable pipelines, and strong experimentation support.
  • Partner closely with product, ML, data science, design, and senior leadership to prioritize roadmaps, navigate tradeoffs, and translate complex platform decisions into measurable business outcomes.
  • Champion engineering excellence through strong practices in system reliability, latency, data integrity, responsible AI development, and operational health across critical marketplace systems.
  • Establish clear operating mechanisms, metrics, and team rhythms that improve execution, support long-range planning, and track platform health, engineering effectiveness, and business impact.
What It Takes to Catch Our Eye
  • Significant experience leading engineering teams in high-scale environments, with a strong track record of delivering search, recommendations, ranking, or retrieval systems that drive meaningful business results.
  • Deep technical fluency in distributed systems, data pipelines, search architecture, and modern machine learning infrastructure, with the ability to guide architecture decisions and mentor senior engineers and managers.
  • Proven success leading integrated teams of software engineers and machine learning engineers while building strong partnerships across product, data science, and executive stakeholders.
  • Ability to operate effectively at multiple altitudes, translating technical depth into strategic clarity and making sound decisions in ambiguous, fast-moving environments.
  • Strong applied understanding of AI-native engineering workflows, including using AI to accelerate design, experimentation, and delivery while ensuring technical accuracy, responsible use, and scalable team adoption.

Come change how the world works.

At Upwork, you'll shape the future of work for a global, remote-first workforce, creating economic opportunities for professionals worldwide. While we have a physical office in Palo Alto, we currently hire full-time employees in 34 U.S. states, making it easier than ever to join our mission from wherever you call home.

Our culture is built on trust, risk-taking, customer focus, and excellence, all in service of our core mission: to create economic opportunities so people have better lives. We embrace authenticity and inclusion, encouraging everyone to bring their whole selves to work. Personal and professional growth is a priority here, supported through development programs, mentorship, and our Upwork Belonging Communities.

We're proud to offer benefits that go beyond the basics, including comprehensive medical coverage for you and your family, unlimited PTO, a 401(k) plan with matching, 12 weeks of paid parental leave, and an Employee Stock Purchase Plan. Visit our Life at Upwork page to learn more about our values, working principles, and the overall employee experience.

Ready to help shape the future of work? Check out our Careers page and follow us on LinkedIn, Facebook, Instagram, TikTok, and X to learn more about life at Upwork.

Upwork is an Equal Opportunity Employer committed to recruiting and retaining a diverse and inclusive workforce. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, or other legally protected characteristics under federal, state, or local law.

Please note that a criminal background check may be required once a conditional job offer is made. Qualified applicants with arrest or conviction records will be considered in accordance with applicable law, including the California Fair Chance Act and local Fair Chance ordinances. The Company is committed to conducting an individualized assessment and giving all individuals a fair opportunity to provide relevant information or context before making any final employment decision.

We use BrightHire, an AI-enabled tool, to record interviews and summarize interview transcripts. The tool allows the interviewer to focus on the discussion and does not score or evaluate candidates or make recommendations. The interview transcripts are reviewed, and decisions are only made by humans. Candidates who prefer not to have their interview recorded through BrightHire can opt out when the interview is scheduled.

To learn more about how Upwork processes and protects your personal information as part of the application process, please review our Global Job Applicant Privacy Notice.