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Remote Audio Machine Learning Jobs in Chicago, IL

Allied

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

POSITION SUMMARY The Senior Machine Learning Engineer is responsible for designing, building, and ... Remote Here at Allied, we believe that great talent can thrive from anywhere. Our remote friendly ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Relativity

Senior Applied Scientist

Chicago, IL · 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

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All JobsAudio Machine Learning JobsRemote Audio Machine Learning JobsRemote Audio Machine Learning Jobs in Chicago, IL

Remote Audio Machine Learning information

See Chicago, IL salary details

$30.4K

$87K

$176.7K

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

As of May 30, 2026, the average yearly pay for remote audio machine learning in Chicago, IL is $87,001.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $116,400.00 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.

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

Senior Machine Learning Engineer

Allied

Chicago, IL • On-site, Remote

$150K - $185K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 28 days ago

Job description

POSITION SUMMARY
The Senior Machine Learning Engineer is responsible for designing, building, and deploying scalable machine learning systems that drive business impact. This role will partner closely with data scientists, AI Technical Product Owners, and engineering teams to integrate machine learning capabilities into real business processes. The emphasis is on operational excellence, scalability, and long-term maintainability rather than research and experimentation.
ESSENTIAL FUNCTIONS
  • Design and implement end to end machine learning pipelines that support data ingestion, feature generation, model training, validation, deployment, and monitoring.
  • Operationalize models in coordination with data scientists and ensure they run reliably with requisite alerts and monitoring in production environments.
  • Build reusable frameworks and patterns that reduce friction when deploying new models or updating existing ones.
  • Ensure pipelines are secure, auditable, and appropriate for use in regulated enterprise environments.
  • Own and evolve the MLOps toolchain that supports model versioning, artifact management, experiment tracking, and deployment workflows.
  • Implement continuous integration and deployment practices for machine learning systems.
  • Establish monitoring and alerting for model performance, data quality, drift, and system health.
  • Partner with cloud and platform teams to manage compute resources, cost controls, and environment configurations.
  • Work with application engineering teams to integrate machine learning outputs into downstream systems and user workflows.
  • Support real time and batch inference patterns depending on business needs.
  • Ensure that machine learning services meet performance, reliability, and availability expectations for production use.
  • Collaborate closely with data scientists to shape models that are production ready and operationally sustainable.
  • Provide guidance on feature engineering, model packaging, and performance tradeoffs from a deployment perspective.
  • Document standards, patterns, and best practices for building and operating machine learning systems.
  • Contribute to the maturation of the organization's overall AI and ML engineering discipline.
  • Other duties as assigned

EDUCATION
  • Bachelor's degree in Computer Science, Math, Statistics, or equivalent work experience required.

EXPERIENCE AND SKILLS:
  • 6+ years of strong experience building and operating machine learning systems in production environments.
  • Solid software engineering skills with Python and familiarity with modern ML frameworks such as PyTorch or TensorFlow.
  • Experience with data pipelines, workflow orchestration, and model deployment patterns.
  • Hands on experience with cloud platforms and managed ML services, with Azure, AWS, and/or Databricks experience preferred.
  • Understanding of MLOps concepts including model versioning, monitoring, testing, and lifecycle management.
  • Experience working with sensitive data in regulated industries such as healthcare or insurance is strongly preferred.
  • Ability to work cross functionally and translate between data science, engineering, and business stakeholders.

POSITION COMPETENCIES
  • Accountability
  • Analytical Problem Solving
  • Collaboration
  • Execution and Delivery
  • Quality and Risk Management
  • Systems Thinking
  • Technical/Functional Expertise

PHYSICAL DEMANDS
  • This is a standard desk role requiring extended sitting and computer work

WORK ENVIRONMENT
  • Remote

Here at Allied, we believe that great talent can thrive from anywhere. Our remote friendly culture offers flexibility and the comfort of working from home, while also ensuring you are set up for success. To support a smooth and efficient remote work experience, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 100Mbps download/25Mbps upload. Reliable internet service is essential for staying connected and productive.
The company has reviewed this job description to ensure that essential functions and basic duties have been included. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills, and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate.
Compensation is not limited to base salary. Allied values our Total Rewards, and offers a competitive Benefit Package including, but not limited to, Medical, Dental, Vision, Life and Disability Insurance, Generous Paid Time Off, Tuition Reimbursement, EAP, and a Technology Stipend.
Allied reserves the right to amend, change, alter, and revise, pay ranges and benefits offerings at any time. All applicants acknowledge that by applying to the position you understand that the specific pay range is contingent upon meeting the qualification and requirements of the role, and for the successful completion of the interview selection and process. It is at the Company's discretion to determine what pay is provided to a candidate within the range associated with the role.

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