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Remote Audio Machine Learning Jobs in Texas (NOW HIRING)

2020 Companies, Inc.

Learning Specialist

Dallas, TX · Remote

Remote - TX - Dallas Overview: As a Learning Specialist at 2020 Companies, you will be responsible ... You will enhance the selling skills of the sales professionals using various resources (audio ...

2020 Companies

Learning Specialist

Dallas, TX · Remote

Remote - TX - Dallas Overview: As a Learning Specialist at 2020 Companies, you will be responsible ... You will enhance the selling skills of the sales professionals using various resources (audio ...

MedReview

Data Scientist

Austin, TX · On-site +1

As a part of our team, you will leverage your analytical skills and expertise in machine learning ... However, for the right fit, we may consider remote . Responsibilities: * Problem Identification:

BNSF Railway

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 ...

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Remote Audio Machine Learning information

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.

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

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.

What is a Remote Audio Machine Learning job?

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 most commonly searched types of Audio Machine Learning jobs in Texas? The most popular types of Audio Machine Learning jobs in Texas are:
What are popular job titles related to Remote Audio Machine Learning jobs in Texas? For Remote Audio Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Remote Audio Machine Learning jobs in Texas look for? The top searched job categories for Remote 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:
Remote Audio Machine Learning jobs near you
Infographic showing various Remote Audio Machine Learning job openings in Texas as of July 2026, with employment types broken down into 78% Full Time, 18% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Staff Machine Learning Engineer - Content and Contributor Intelligence (Remote - United States)

Staff Machine Learning Engineer - Content and Contributor Intelligence (Remote - United States)

Yelp, Inc

Austin, TX • Remote

Full-time

Re-posted 23 days ago

Yelp rating

7.8

Company rating: 7.8 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

108th of 205 rated software companies

Job description

Summary

Yelp engineering culture is driven by our values: we're a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we're all about helping our users, growing as engineers, and having fun in a collaborative environment.

Yelp's mission of connecting people with great local businesses requires the use of cutting-edge Machine Learning (ML) and Artificial Intelligence (AI) to scale across a vast and diverse base of users and businesses spanning various geographical locations. As a Staff-level ML Engineer on the Content Contributor Intelligence team, you will help build connections across millions of users and business listings. Your work will involve using cutting-edge industry tools, including neural networks (NNs), large language models (LLMs), and various embedding techniques for text, images, and videos. Additionally, you will apply traditional ML methods such as XGBoost and linear models to enhance our systems.  You'll be responsible for turning raw data into valuable signals and building ML systems end-to-end. This includes the full ML lifecycle from training models to deploying them in production, as well as contributing to the ML platforms these models rely on. 

This opportunity is fully remote and does not require you to be located in any particular state within the US. We welcome applicants from throughout the US. We'd love to have you apply, even if you don't feel you meet every single requirement in this posting. At Yelp, we're looking for great people, not just those who simply check off all the boxes.

What you'll do:
  • Conduct end-to-end analyses, wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
  • Mentor and guide junior engineers, fostering a culture of learning and technical excellence.
  • Work with large and complex textual and visual datasets.
  • Support the development and deployment of projects involving machine learned models for offline, batch-based data products as well as models deployed to online, real-time services.
  • Work in the contributor and visual intelligence team on text and visual understanding, along with fine tuning transformer models to derive embeddings for multiple input types
  • Productionize and automate model pipelines within Python services.
  • Drive and advocate adoption of best practices in ML development and operations, and mentor newer engineers in those practices.
What it takes to succeed:
  • Experience developing and productionizing machine learning models, particularly in neural networks, computer vision and LLMs including their supported data pipelines.
  • Experience with machine learning using packages such as PyTorch, TensorFlow, Spark MLlib, XGBoost, and Sklearn.
  • Strong coding skills in Python or equivalent (Java, C++).
  • Solid understanding of engineering and infrastructure best practices.
  • The curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal.
  • We highly value experience of working with LLMs, utilizing LLM APIs (OpenAI, Bedrock, etc), prompt engineering and evaluation.
  • A Bachelor's Degree or an equivalent work experience is required
What you'll get:
  • There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience. Based on the anticipated level of experience we are seeking, we expect the compensation range for this role to be between $112,000 and $269,000. You may also be offered a bonus, restricted stock units, and benefits.
  • This opportunity has the option to be fully remote in all locations across the US.
  • You can find more information about Yelp's five star benefits here!
ClosingAt Yelp, we believe that diversity is an expression of all the unique characteristics that make us human: race, age, sexual orientation, gender identity, religion, disability, and education - and those are just a few. We recognize that diverse backgrounds and perspectives strengthen our teams and our product. The foundation of our diversity efforts are closely tied to our core values, which include "Playing Well With Others" and "Authenticity." We're proud to be an equal opportunity employer and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition or disability. Actual salary offered may vary based on multiple factors, including but not limited to, an individual's location and experience.  We will consider for employment qualified candidates with arrest and conviction records, consistent with applicable law (including, for example, the San Francisco Fair Chance Ordinance for roles based in San Francisco, the Los Angeles County Fair Chance Ordinance for roles based in the unincorporated areas of Los Angeles County, and the California Fair Chance Act for roles based in California). Where required by law, a criminal background check will not be conducted until after a conditional offer of employment is made, and any evaluation of a candidate's criminal background check will be subject to an individualized assessment that takes into account the candidate's specific criminal records and the responsibilities and requirements of the particular role. We are committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, you may contact us at accommodations-recruiting@yelp.com or 415-969-8488. Note: Yelp does not accept agency resumes. Please do not forward resumes to any recruiting alias or employee. Yelp is not responsible for any fees related to unsolicited resumes. #LI-Remote 

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Employment Type: FULL_TIME

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Benefits

Hours and flexibility

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