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Remote Audio Machine Learning Jobs in Texas (NOW HIRING)

BNSF Railway

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

Remote US Anticipated Start Date: 06/01/2026 The US base salary range for this full-time position ... Lead the development and deployment of advanced machine learning models to forecast outcomes and ...

Vogo

Data Scientist

Dallas, TX · On-site +1

From downtown hotels and luxury resorts to private vacation rentals and remote cabins, Vogo offers ... This role will own the Machine Learning models that drive our business from development to ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116.40K - $198.20K/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 ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116.40K - $198.20K/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 ...

Blue Cross of Idaho

AI Technical Lead

Meridian, TX · On-site +1

... 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.

Zantech

Data Analyst

San Antonio, TX · Remote

Perform remote data collection, cleaning, transformation, and analysis * Apply statistical methods and machine learning techniques to datasets * Develop visualizations and dashboards using Tableau ...

Maximus

AI/ML Software Developer

San Antonio, TX · On-site +1

This position is remote and requires a Secret clearance or higher. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

Zantech

Data Analyst

San Antonio, TX · On-site +1

Perform remote data collection, cleaning, transformation, and analysis * Apply statistical methods and machine learning techniques to datasets * Develop visualizations and dashboards using Tableau ...

Relativity

Senior Applied Scientist

Houston, TX · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Develop machine learning and generative AI models that ship as customer-facing product features

HiddenLayer

AI Red Teamer

Austin, TX · On-site +1

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 ...

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · Remote

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

Gainwell Technologies LLC

Principal Data Sciences

Dallas, TX · On-site +1

$124K - $177.10K/yr

... machine learning and AI solutions using python * Experience with data cleansing, validation, and general quality control principals What you should expect in this role * Fully Remote Opportunity - Wo ...

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All JobsRemote Audio Machine Learning JobsRemote Audio Machine Learning Jobs in Texas

Remote Audio Machine Learning information

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.

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 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 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 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 May 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 37% Physical, 3% Hybrid, and 60% Remote job distribution.
Data Scientist - Remote

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Posted 26 days ago

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

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NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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