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Remote Audio Machine Learning Jobs in New York (NOW HIRING)

Alignerr

Machine Learning Engineer

Manhattan, NY · Remote

$154K/yr

Machine Learning Engineer (AI Data Trainer) About the Role What if your machine learning expertise ... Remote * Commitment : 10-40 hours/week What You'll Do * Construct precise, well-structured ...

Inizio Partners

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

Location- Remote Overview: As a GCP ML Engineer, you'll design, develop, and maintain machine learning pipelines and infrastructure on the Google Cloud Platform (GCP). You'll work closely with data ...

Finch Services

Machine Learning Engineer

Manhattan, NY · On-site +1

$180K - $280K/yr

As a Machine Learning Engineer at Finch, you'll own the full lifecycle of AI systems, from ... for a remote-first role -- this one is 4 days/week in our NYC office. Compensation The expected ...

Alignerr

Senior Machine Learning Expert

Manhattan, NY · Remote

$95K - $118K/yr

Senior Machine Learning Expert (AI Training) About the Role What if your deep expertise in machine ... This is a fully remote, flexible contract role built for senior-level ML professionals who ...

Autodesk

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/yr

This role is currently open to remote work. Candidates must be located near one of our hub ... Design and implement machine learning capabilities that improve Autodesk's customer-facing ...

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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 New York? The most popular types of Audio Machine Learning jobs in New York are:
What are popular job titles related to Remote Audio Machine Learning jobs in New York? For Remote Audio Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Remote Audio Machine Learning jobs in New York look for? The top searched job categories for Remote Audio Machine Learning jobs in New York are:
What cities in New York are hiring for Remote Audio Machine Learning jobs? Cities in New York with the most Remote Audio Machine Learning job openings:
Remote Audio Machine Learning jobs near you

Remote Machine Learning Engineer

Angenex

Jersey City, NJ • Remote

Other

Posted 15 days ago

Job description

Remote Machine Learning Engineer

Jersey City, NJ, United States

About the Job

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.

Responsibilities

- Build and deploy the ML pipelines that power the company machine learning platform.

- Manage MLOps infrastructure to monitor and optimize models.

Qualifications

Experience:

1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Proficiency across topics in machine learning and statistics.

Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.

Familiarity with CNNs, RNN, LSTMs, and the latest research trends.

Experience implementing, deploying, and maintaining production machine learning systems.

Experience monitoring and optimizing model performance.

Experience with Linux, Docker and AWS, and basic development operations.

Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

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