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Audio Machine Learning Jobs in Chicago, IL (NOW HIRING)

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Audio Machine Learning information

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$30.4K

$87K

$176.7K

How much do audio machine learning jobs pay per year?

As of Jul 13, 2026, the average yearly pay for 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 in the Audio Machine Learning position, and why are they important?

To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.

Will MLE be replaced by AI?

In the context of an Audio Machine Learning (ML) role, AI tools and automation are increasingly used to assist with tasks like data processing and model deployment. However, MLE professionals are essential for designing, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Human expertise remains critical for interpreting results and ensuring system performance.

What are the typical daily responsibilities of someone working in Audio Machine Learning?

Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.

What is an Audio Machine Learning job?

An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.

Which 5 jobs will survive AI?

Audio Machine Learning specialists are likely to continue in demand as AI advances because their expertise in developing and refining audio recognition systems requires specialized skills that are difficult to automate fully. Roles involving creative audio design, audio engineering, and human oversight of AI systems are also expected to persist. These jobs often require a combination of technical knowledge, domain expertise, and critical thinking that AI cannot easily replace.

What engineer makes $500,000 a year?

Senior audio machine learning engineers with extensive experience, advanced skills in deep learning and signal processing, and often working at large tech companies or specialized research labs can earn salaries approaching or exceeding $500,000 annually. Compensation typically includes base salary, bonuses, and stock options, especially in high-demand industries like AI and audio processing.

Do audio engineers get paid well?

Audio engineers typically earn competitive salaries that vary based on experience, location, and industry sector. Entry-level positions may start lower, but experienced professionals working in recording studios, broadcasting, or live sound often have higher earnings, especially with specialized skills and certifications. Overall, the profession offers the potential for good compensation, particularly for those with technical expertise and a strong portfolio.
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 Audio Machine Learning jobs in Chicago, IL? For Audio Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Audio Machine Learning jobs in Chicago, IL look for? The top searched job categories for Audio Machine Learning jobs in Chicago, IL are:
Project Perseus \u007C Speech & Voice AI Analyst - Portuguese (Portugal) Speakers

Project Perseus \u007C Speech & Voice AI Analyst - Portuguese (Portugal) Speakers

Welo Data

Chicago, IL • On-site

$34/hr

Full-time

Re-posted 17 days ago


Job description

Overview

Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems.

This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs.

While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale.

We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.

Project Details
  • Job Title: Data Labeling Analyst
  • Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent) 
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $34/hour
Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.
What You’ll Do
  • Execute high-volume data labeling and annotation tasks across speech and voice datasets
  • Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
  • Work with audio and language data, including transcription, categorization, and tagging
  • Maintain strong throughput while meeting quality expectations
  • Escalate unclear or ambiguous cases appropriately
  • Adapt to evolving guidelines and workflows as systems and requirements change
  • Support baseline data production needs for AI training pipelines
  • Contribute to team calibrations and quality alignment sessions 
What We’re Looking For
  • Native-level fluency in Portuguese (Portugal)
  • Strong written communication skills and language fundamentals
  • 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field.
  • Ability to follow detailed instructions and apply guidelines consistently
  • High attention to detail and ability to maintain accuracy in repetitive tasks
  • Comfort working in structured, process-driven environments
  • Ability to manage time effectively and maintain steady output
  • Willingness to ask questions and escalate when needed
  • Basic familiarity with AI, speech technology, or language data is a plus 
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)
Onsite Perks (where applicable):
Free breakfast, lunch, and dinner
Stocked micro-kitchens with snacks and beverages
Commuter benefits, including shuttles and bike-to-work options
Unique campus features depending on location
Why This Role

This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users.

It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.


Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
 
To know more details (Click here)
 
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.
 
 
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
 
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.


Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.