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Assistant Machine Learning Quant Jobs in Chicago, IL

DRW

Quantitative Researcher

Chicago, IL · On-site

$250K - $300K/yr

As a Quantitative Researcher , you will develop mathematical models using advanced statistical ... machine learning techniques * Assist software developers to translate research strategies into ...

Until

Machine Learning Engineer / Scientist

Mundelein, IL

$140K - $240K/yr

About the Role As a Machine Learning Engineer / Scientist at Until, you will be an early member of ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Optiver

Quantitative Intern (Summer 2027)

Chicago, IL · On-site +1

... Quant Research internship offer. What You'll Do: Our internship is designed for curious problem-solvers who enjoy continuously learning. Through a combination of structured education, market ...

Optiver

Quantitative Intern (Summer 2027)

Chicago, IL · On-site

$70K - $88K/yr

... Quant Research internship offer. What You'll Do: Our internship is designed for curious problem-solvers who enjoy continuously learning. Through a combination of structured education, market ...

IMC

Quantitative Researcher - Futures

Chicago, IL

... machine learning techniques to derive forecasts that will be combined with IMC's best-in-class ... Several years (5+ Years) of quantitative research experience, preferably in systematic trading ...

Akuna Capital

Quantitative Research Intern

Chicago, IL · On-site

$130K/yr

Develop trading strategies using statistical and machine learning algorithms. * Design and implement optimization algorithms for portfolio construction. * Develop quantitative models describing ...

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Assistant Machine Learning Quant information

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How much do assistant machine learning quant jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for assistant machine learning quant in Chicago, IL is $18.60, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $19.81 per hour, depending on experience, location, and employer.

What is an assistant machine learning quant?

Assistant Machine Learning Quants are entry-level professionals in quantitative finance who support senior quants by applying machine learning techniques to analyze financial data, build predictive models, and develop trading strategies. Their responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They work closely with quantitative researchers and traders to improve algorithmic trading systems and risk management processes. This role typically requires strong programming skills, a solid understanding of machine learning concepts, and familiarity with financial markets.

How does an assistant machine learning quant typically collaborate with senior quants and data scientists on projects?

As an Assistant Machine Learning Quant, you will often work closely with senior quantitative researchers and data scientists by supporting model development, data preprocessing, and feature engineering tasks. You may contribute to brainstorming sessions, implement prototypes, and assist in backtesting trading strategies or risk models. This collaborative environment provides valuable mentorship opportunities and exposure to best practices in quantitative analysis and machine learning within the finance industry. Effective communication and a willingness to learn from senior team members are key to success in this role.

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

To thrive as an Assistant Machine Learning Quant, you need strong quantitative skills, a background in statistics or mathematics, and typically a degree in a STEM field. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate model development, efficient data analysis, and clear collaboration with team members in high-stakes financial environments.
What are the most commonly searched types of Machine Learning Quant jobs in Chicago, IL? The most popular types of Machine Learning Quant jobs in Chicago, IL are:
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Assistant Machine Learning Quant jobs near you
Infographic showing various Assistant Machine Learning Quant job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $38,682 per year, or $18.6 per hour.

Hardware Machine Learning PhD Research Internship

IMC Trading

Chicago, IL

$225K/yr

Full-time, Internship

PTO

Posted 21 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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