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Remote Audio 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 ...

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 ...

Senior Software Engineer - Remote

Austin, TX · Remote

$121K - $160K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Senior Software Engineer - Remote

Texas City, TX · Remote

$104K - $138K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

... 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.

Showing results 21-40

Remote Audio Machine Learning information

What is a remote audio machine learning?

A Remote Audio Machine Learning job involves using machine learning techniques to analyze, process, or generate audio data while working from a remote location. Professionals in this field develop algorithms for tasks such as speech recognition, music classification, noise reduction, or audio synthesis. They often work with large datasets, build and train models, and collaborate with teams online. These roles typically require skills in programming, signal processing, and experience with machine learning frameworks.

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

To thrive as a Remote Audio Machine Learning Engineer, you need strong foundations in digital signal processing, machine learning algorithms, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, and audio processing libraries (e.g., LibROSA), as well as experience with cloud platforms, is highly valuable. Excellent problem-solving skills, self-motivation, and clear remote communication are essential soft skills for collaborating across distributed teams. These competencies enable the development of robust, innovative audio ML solutions while ensuring effective teamwork and project delivery in a remote setting.

How does a remote audio machine learning role typically collaborate with cross-functional teams, and what communication tools are commonly used?

In a Remote Audio Machine Learning position, collaboration with cross-functional teams such as software engineers, data scientists, and product managers is essential. Regular communication is maintained through tools like Slack, Zoom, and project management platforms such as Jira or Trello. Team members often participate in virtual stand-ups, sprint planning sessions, and code reviews to ensure alignment on project goals and timelines. Effective asynchronous communication and clear documentation are especially important in remote settings to keep everyone informed and foster a productive workflow.

What is the difference between Remote Audio Machine Learning vs Remote Audio Engineer?

AspectRemote Audio Machine LearningRemote Audio Engineer
Required CredentialsBackground in machine learning, data science, or AI; often a degree in computer science or related fieldsAudio engineering, sound design, or music production degree or certification
Work EnvironmentPrimarily focused on developing algorithms, data analysis, and model training, often in a tech or research settingRecording, mixing, editing audio, often in studios or remote production setups
Employer & Industry UsageTech companies, research labs, AI startups working on audio recognition or enhancementMusic, film, broadcasting, and media production companies

Remote Audio Machine Learning specialists focus on developing algorithms to process and analyze audio data, while Remote Audio Engineers handle the practical aspects of recording and editing sound. Both roles may collaborate but serve different functions within the audio industry.

What are the most commonly searched types of Audio Machine Learning jobs in Texas?

The most popular types of Audio Machine Learning jobs in Texas are:

What cities in Texas are hiring for Remote Audio Machine Learning jobs?

Cities in Texas with the most Remote Audio Machine Learning job openings:

Infographic showing various Remote Audio Machine Learning job openings in Texas as of August 2026, with employment types broken down into 27% Internship, and 73% Full Time. Highlights an 100% Remote job distribution.

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.