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Remote Audio Machine Learning Jobs in Ashburn, VA

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Senior Machine Learning Engineer

Arlington, VA · On-site +1

$120K - $165K/yr

This role is a full-time position based in our Pittsburgh, PA office or open to Remote ... machine learning systems, ML infrastructure, distributed systems, or similar technical systems.

SAIC

AI Machine Learning Developer Principal

Chantilly, VA · On-site +1

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

SAIC

AI Machine Learning Developer Principal

Arlington, VA · On-site +1

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

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Showing results 21-40

All JobsAudio Machine Learning JobsRemote Audio Machine Learning JobsRemote Audio Machine Learning Jobs in Ashburn, VA

Remote Audio Machine Learning information

See Ashburn, VA salary details

$30.2K

$86.4K

$175.4K

How much do remote audio machine learning jobs pay per year?

As of Sep 12, 2026, the average yearly pay for remote audio machine learning in Ashburn, VA is $86,365.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,100.00 and $115,600.00 per year, depending on experience, location, and employer.

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 popular job titles related to Remote Audio Machine Learning jobs in Ashburn, VA?

For Remote Audio Machine Learning jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Remote Audio Machine Learning jobs in Ashburn, VA look for?

The top searched job categories for Remote Audio Machine Learning jobs in Ashburn, VA are:

Remote Audio Machine Learning jobs near you
Infographic showing various Remote Audio Machine Learning job openings in Ashburn, VA as of August 2026, with employment types broken down into 28% Internship, and 72% Full Time. Highlights an 100% Remote job distribution, with an average salary of $86,365 per year, or $41.5 per hour.

Machine learning Engineer & AI Platform Developer - 10+years of experirnce

Herndon, VA • Remote

Two95 International Inc.
Recruiting and Staffing Services • 11 - 50 employees
Learn more about Two95 International Inc.external

Contractor

Re-posted 26 days ago

Job description

Job Title: Machine Learning Engineer & AI Platform Developer - 10+years experience

Location: Remote

Type: Full-Time

Job Description:

We are looking for a talented Machine Learning Engineer & AI Platform Developer to join our team. In this role, you will be responsible for designing, developing, and deploying machine learning models and AI applications. You will work closely with data scientists, software engineers, and other stakeholders to implement AI solutions that meet business needs.

Key Responsibilities:

  • Design and develop machine learning models and AI platforms to solve complex problems.
  • Work with large datasets to preprocess, analyze, and derive insights using machine learning techniques.
  • Implement and deploy scalable machine learning solutions using cloud platforms (e.g., AWS, GCP, Azure).
  • Collaborate with cross-functional teams to integrate machine learning models into existing applications.
  • Optimize and monitor model performance, making improvements as necessary.
  • Stay current with emerging AI technologies and best practices to drive continuous improvement.
  • Document processes, code, and model performance for future reference.

Requirements

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.
  • Proven experience as a Machine Learning Engineer or similar role (3+ years preferred).
  • Strong programming skills in Python, R, or Java, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying AI solutions.
  • Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
  • Solid understanding of algorithms, data structures, and software engineering principles.
  • Excellent analytical, problem-solving, and communication skills.
  • Ability to work collaboratively in a fast-paced environment.
TWO95 International logo

About TWO95 International

Sourced by ZipRecruiter

At TWO95 International, we believe it is imperative that a hiring company is assured of procuring the right candidate to fill a job requirement. We have an extensive local and International network, and a fully digitalized sourcing approach that allows us to find a candidate best suited for the job. Furthermore, we strive to secure well matched opportunities that align with the personal and career aspirations of our candidates.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Cherry Hill, NJ, US

Year founded

2009

Social media

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