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Remote Audio Machine Learning Jobs in Illinois (NOW HIRING)

Machine Learning Engineer

Chicago, IL · On-site +1

$95 - $105/hr

... to remote, hybrid, or onsite candidates. Hiring Process - Target start dates are still being ... Applying the latest techniques and approaches across the domains of data science, machine learning ...

New

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

TEKsystems is seeking a Machine Learning Engineer to support one of our major customers that sits ... THIS IS 100% REMOTE and LONG TERM. Top 3-5 Skills - Strong engineering foundation. - Ability to ...

New

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 ...

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Showing results 1-20

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 Illinois? The most popular types of Audio Machine Learning jobs in Illinois are:
What cities in Illinois are hiring for Remote Audio Machine Learning jobs? Cities in Illinois with the most Remote Audio Machine Learning job openings:

Machine Learning Engineer

TEKsystems

Chicago, IL • On-site, Remote

$95 - $105/hr

Contractor

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

Description

Supplier Call notes

Sr. ML Engineer – AI Space

Posting new job description.

Additional Role

- Same requirements as the previous opening.

- Additional projects and initiatives driving the need.

- Recently onboarded a person for a previous role but have not filled all of the openings yet.

Top 3–5 Skills

- Strong engineering foundation.

- Ability to understand the problem.

- Ability to approach problems systematically.

- Ability to learn new technologies on the job.

- Some experience with ML technologies, particularly from an engineering perspective.

- Will be using existing models to create software services, not writing research papers.

- Cloud engineering experience is required.

- Thinks systematically.

- Open to remote, hybrid, or onsite candidates.

Hiring Process

- Target start dates are still being discussed.

- Interviews will begin next week and continue on an ongoing basis.

- Initial phone screen with Vladimir.

- Followed by interviews with technical members of the team.

- Decision made after the interview process.

Ideal Profile

- Looking for candidates from strong technology companies.

- Example profile: graduate from UCLA with 2–3 years at Snapchat in the ML domain, or experience with Walmart eCommerce.

- Will begin removing profiles from consideration today.

- Technical understanding

Experience building ML systems such as:

- ML pipelines

- Real-time inference services

- Working with and maintaining feature stores

- Strong foundation in AWS cloud infrastructure.

- Top priority is a solid engineering experience.

- Seems to value candidates with a strong college history and the ability to clearly describe their experience and technical foundation.

Culture

- Each person is assigned to a specific project and focuses on one task at a time.

- Agile software development environment.

- Daily stand-ups to exchange updates and discuss progress.

Onboarding

- New hires receive an onboarding buddy who helps show them the ropes.

- Ramp-up period is typically 1–3 weeks.

- After onboarding, they begin receiving small, simple tasks to continue ramping up.

- By the second month, they should be able to deliver practical, smaller tasks independently.

- By 90 days, they should be able to take responsibility for a specific area of

Description:

PURPOSE:

At Hyatt, we’re working to Advance Care through data-driven decisions and automation. This mission serves as the foundation for every decision as we create the future of travel. We can’t do that without the best talent – talent that is innovative, curious, and driven to create exceptional experiences for our guests, customers, owners and colleagues.  

Hyatt seeks an extraordinary Machine Learning Engineer to help build the algorithmic assets and features that Hyatt guests, members, customers and internal users leverage to transform the guest experience and drive efficiencies across the operations of our business.

In this role you will design and implement algorithmic product architectures to bring our machine learning models to life across the full lifecycle of the product including data ingestion, ML processing, and results delivery/activation. This role will work cross-functionally with various data science teams, data engineering teams, and data architecture teams. The ideal candidate can serve as both solutions architect as well as hands-on implementation engineer and guide the team towards best-in-class algorithmic product implementations.

You will be a part of a ground-floor, hands-on, highly visible team which is positioned for growth and is highly collaborative and passionate about data science.

Applying the latest techniques and approaches across the domains of data science, machine learning, and AI isn’t just a nice to have, it’s a must.

POSITION RESPONSIBILITIES:

• Partner with data scientists to design workflows/architectures that activate ML models and maximize their impact, such as real-time streaming use-cases and offline batch optimizations.

• Partner with data scientists to develop prototype solutions of algorithmic products leveraging appropriate AWS services with appropriate consideration for scale and latency where applicable.

• Implement and productionize final solutions via infrastructure-as-code pattern.

• Implement data processing workflows to enhance our Feature Store with impactful data including appropriate data cleansing/imputation logic.

• Enhance existing algorithmic products architecture/workflow as needed to maximize impact of the algorithmic product.

• Partner with data engineering team to ensure data science data needs are being delivered in the appropriate format/cadence required for maximum impact.

• Stay up to date with latest design patterns and AWS services with respect to Machine Learning Engineering.

• Partner with data architecture, data governance, and security team to ensure solutions meet required standards.

The ideal candidate demonstrates a commitment to Hyatt core values: respect, integrity, humility, empathy, creativity, and fun.

EXPERIENCE AND QUALIFICATIONS:

• 5+ years of implementing software product solutions in a cloud environment with a focus on algorithmic/machine learning products, hospitality experience not required

• Expertise in AWS cloud services

• Expertise in Python, SQL, PySpark, Docker

• Experience with streaming and batch data architectures at scale

• Experience operating in an Agile Methodology environment.

• Experience with DevOps and CI/CD concepts

• Excellent communication and teamwork skills

• Position will not require customer-facing interactions.

EDUCATION:

master’s degree in computer science, software engineering, or related fields required

Skills

sagemaker, AWS, Python, SQL

Top Skills Details

sagemaker,AWS,Python,SQL

Experience Level

Intermediate Level

Job Type & Location

This is a Contract position based out of Chicago, IL.

Pay and Benefits

The pay range for this position is $95.00 - $105.00/hr.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following: • Medical, dental & vision • Critical Illness, Accident, and Hospital • 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available • Life Insurance (Voluntary Life & AD&D for the employee and dependents) • Short and long-term disability • Health Spending Account (HSA) • Transportation benefits • Employee Assistance Program • Time Off/Leave (PTO, Vacation or Sick Leave)

Workplace Type

This is a fully remote position.

Application Deadline

This position is anticipated to close on Jul 31, 2026.

About TEKsystems

We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.

The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

About TEKsystems and TEKsystems Global Services

We’re a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. We’re a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. We’re strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. We’re building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com.

The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.

Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.