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Audio Machine Learning Intern Jobs in Chicago, IL

Optiver

Quantitative Research Intern (PhD)

Chicago, IL

$80K - $90K/yr

Using statistical models and machine learning to develop trading algorithms. * Leveraging big data ... Available to intern during Summer 2026 * Open to full-time opportunities upon graduation in 2027 or ...

Optiver

Quantitative Research Intern PhD

Chicago, IL · On-site

$80K - $90K/yr

Using statistical models and machine learning to develop trading algorithms. * Leveraging big data ... Available to intern during Summer 2026 * Open to full-time opportunities upon graduation in 2027 or ...

Optiver

Quantitative Research Intern (PhD)

Chicago, IL · On-site

$80K - $90K/yr

Using statistical models and machine learning to develop trading algorithms. * Leveraging big data ... Available to intern during Summer 2026 * Open to full-time opportunities upon graduation in 2027 or ...

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All JobsAudio Machine Learning Intern JobsAudio Machine Learning Intern Jobs in Chicago, IL

Audio Machine Learning Intern information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

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

As of Aug 6, 2026, the average yearly pay for audio machine learning intern in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

What does an audio machine learning intern do?

An Audio Machine Learning Intern assists in developing and improving machine learning models that process and analyze audio data. Their tasks may include data preprocessing, feature extraction, model training, and evaluation for applications like speech recognition, sound classification, or music analysis. Interns often collaborate with engineers and researchers to experiment with new algorithms and optimize audio-based AI systems. This role provides hands-on experience in both audio signal processing and machine learning techniques.

What types of projects can an audio machine learning intern expect to work on during their internship?

As an Audio Machine Learning Intern, you can expect to be involved in projects such as developing and fine-tuning audio classification models, working on speech recognition algorithms, or improving the accuracy of sound event detection systems. You may also assist with the collection and preprocessing of audio datasets, as well as support model evaluation and optimization. Collaboration with data scientists, audio engineers, and software developers is common, offering a hands-on learning environment and exposure to end-to-end machine learning workflows in the audio domain.

What are the key skills and qualifications needed to thrive as an audio machine learning intern, and why are they important?

To thrive as an Audio Machine Learning Intern, you need a solid background in signal processing, machine learning fundamentals, and programming skills, often supported by coursework or research in computer science or electrical engineering. Familiarity with Python, TensorFlow or PyTorch, and audio processing libraries like Librosa is typically required. Creativity, problem-solving abilities, and strong collaboration skills help you stand out in this role. These skills are crucial for developing innovative audio solutions, interpreting complex data, and working effectively within research or product teams.

What is the difference between Audio Machine Learning Intern vs Audio Data Analyst?

AspectAudio Machine Learning InternAudio Data Analyst
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fieldsDegree in Data Analysis, Statistics, or related fields; may have certifications in data tools
Work EnvironmentResearch labs, tech companies, or startups focusing on AI and audio techData-driven departments within media, entertainment, or tech companies
Employer & Industry UsageUsed in AI development, research projects, and product innovationUsed for analyzing audio data, improving user experience, and reporting

The Audio Machine Learning Intern focuses on developing models and algorithms for audio data, often in research or development settings. In contrast, the Audio Data Analyst primarily interprets audio data to generate insights and support decision-making. Both roles require familiarity with audio data, but the intern role emphasizes machine learning skills, while the analyst role centers on data analysis and reporting.

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:
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What job categories do people searching Audio Machine Learning Intern jobs in Chicago, IL look for? The top searched job categories for Audio Machine Learning Intern jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Audio Machine Learning Intern jobs? Cities near Chicago, IL with the most Audio Machine Learning Intern job openings:
Audio Machine Learning Intern jobs near you

Hardware Machine Learning PhD Research Internship

IMC Trading

Chicago, IL

$225K/yr

Full-time, Internship

PTO

Posted 19 days ago

Job description

We are deploying machine learning directly onto custom hardware - and we want you to help drive it forward. This PhD internship is an opportunity to work on research that has direct impact on IMC's work tackling open problems at the frontier of low-latency ML inference and hardware acceleration.

You'll work alongside IMC engineers in one of the most demanding low-latency computing environments in the world. You'll own a focused research project from start to finish, present your findings to the team, and leave behind a prototype or benchmark that we can build on.

Your Core Responsibilities

  • Architect and develop an ML focused research project based on real-world use cases
  • Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions
  • Track and evaluate emerging research in neural architecture search, machine learning systems and quantization methods, and determine what translates to measurable improvements in our systems
  • Present your project to the team, deepening our collective understanding of an area of ML acceleration
  • Gain hardware design fundamentals from skilled RTL developers and learn how they apply to our industry
  • Build skills to evaluate research not only from an academic perspective, but through real-world performance constraints, engineering costs, and industry impact

Your Skills and Experience

  • Currently enrolled in a PhD program in Electrical Engineering, Computer Science, Physics, or a related field
  • Solid understanding of hardware constraints and design trade-offs (e.g., pipelining, resource utilization, fixed-point arithmetic) that shape how ML models can be efficiently mapped onto FPGAs or custom ASICs
  • Experience with hardware fundamentals, whether through VHDL/SystemVerilog development, HLS tools, or ML-to-hardware frameworks like hls4ml, FINN, or Vitis AI
  • Understanding of machine learning fundamentals - neural network architectures, inference optimization, quantization techniques, ML frameworks such as PyTorch/TensorFlow
  • Proficiency in Python or similar languages for tooling, testing, and simulation
  • Strong communication skills and ability to work collaboratively across disciplines with both technical and non-technical teams

You may submit one application per role each year. We strongly encourage you to focus on applying to a single role that best matches your skills and interests. Though you may apply to multiple roles, please note that each application will be evaluated based on the specific criteria established for that particular role. If you have already applied for this position during the current recruitment season and were not selected, you may reapply when the next recruitment season begins in 2027.

The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.

Base Salary: $225,000

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

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