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Remote Audio Machine Learning Jobs in Darien, CT

10a Labs

Machine Learning Engineer

New York, NY · Remote

$150K - $250K/yr

Vision, audio, OCR, or deepfake classification. * Designing multilingual embedding systems with ... Fully remote, U.S.-based. * Health Benefits: Comprehensive health, dental, and vision coverage.

Mercor

Machine Learning Engineer

New York, NY · Remote

$27 - $32/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close knowledge gaps in data science , AI , and machine learning domains. Surface nuances that ...

Mercor

Machine Learning Engineer

New York, NY · Remote

$70 - $100/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to ... experience in Machine Learning , Data Science , Software Engineering , Computer Science ...

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All JobsAudio Machine Learning JobsRemote Audio Machine Learning JobsRemote Audio Machine Learning Jobs in Darien, CT

Remote Audio Machine Learning information

See Darien, CT salary details

$30.8K

$88.1K

$178.9K

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

As of May 31, 2026, the average yearly pay for remote audio machine learning in Darien, CT is $88,089.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,200.00 and $117,900.00 per year, depending on experience, location, and employer.

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.

Remote Audio Machine Learning jobs near you
Senior Machine Learning Engineer (Remote)

Senior Machine Learning Engineer (Remote)

Zencastr

New York, NY • On-site, Remote

$114.30K - $157K/yr

Full-time

Posted 12 days ago

Job description

The Role
We build end-to-end AI systems, core microservices, and infrastructures by leveraging cutting-edge technologies to impact millions with personalized user experiences everyday.
We are looking for an outstanding machine learning engineer to join our team! The role will provide an opportunity to work on large scale machine learning to improve the podcast creation experience at Zencastr.
You'll join a team of hardworking engineers that are passionate about understanding what drives users' long-term happiness with Zencastr, and how our recommendations and content affects that. As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers in prototyping and productizing brand-new ML at the intersection of speech processing and long-term user satisfaction.
What You'll Do..
  • Design, research and develop state-of-the-art machine learning applications and algorithms to improve the lives of podcasters and podcast listeners around the world
  • Collaborate with engineering partners and colleagues in large multi-functional efforts to build new product features that advise and enrich Zencastr's various ML services.
  • Drive forward audio and text capabilities within the ML team
  • Work with some of the brightest minds in signal processing

If This Describes You..
  • A postgraduate degree in Machine Learning, Mathematics, Computer Science, or a related quantitative field
  • 5 + years experience in Python
  • 3+ years experience in machine learning research, with a focus on speech
  • 3+ years experience training or deploying neural networks
  • Significant experience with machine learning libraries like PyTorch, Tensorflow, Scikit-Learn
  • Experience with building and operating production-ready ML systems
  • Ability to lead design and implementation of major software components, systems, and features
  • You enjoy quickly building model prototypes
  • Experience with cloud technologies (Google Cloud, AWS, Modal)
  • You are a self-starter who drives your own projects and builds positive relationships with partners and colleagues to solve big multi-functional efforts from start to finish. You are able to succeed with minimal mentorship and process.

Bonus points if you have:
  • Publications in peer-reviewed journals from a related field
  • Experience with modern speech processing frameworks
  • Good dev ops experience
  • Advanced DSP experience
  • MongoDB or SQL experience
  • Experience with unit, integration, and load testing
  • Experience building APIs
  • Experience with Docker containers, Implementing Docker Containers, Container Clustering
  • Experience with container orchestration technology such as Kubernetes a big plus

How to apply:
Apply at https://jobs.ashbyhq.com/zencastr/c6a9c3b0-f260-4820-bb97-e78142eabd1e
We are flexible! For the right candidate we ask: What do you need to do your best work?

Apply