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

The role involves designing and deploying machine learning models, collaborating with trading teams ... Required : โ€ข PhD or Master's in Engineering, Math, Statistics, Computer Science, or related ...

Design and deploy machine learning models to enhance trading performance across various asset ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

Machine Learning Researcher

Chicago, IL ยท On-site

$250K - $300K/yr

Design and deploy machine learning models to enhance trading performance across various asset ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

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Phd Machine Learning information

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How much do phd machine learning jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for phd machine learning in Chicago, IL is $23.53, according to ZipRecruiter salary data. Most workers in this role earn between $20.34 and $26.25 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional, and why are they important?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

What is the difference between Phd Machine Learning vs Data Scientist?

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities near Chicago, IL are hiring for Phd Machine Learning jobs? Cities near Chicago, IL with the most Phd Machine Learning job openings:
Infographic showing various Phd Machine Learning job openings in Chicago, IL as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $48,938 per year, or $23.5 per hour.
Hardware Machine Learning PhD Research Internship

Hardware Machine Learning PhD Research Internship

IMC

Chicago, IL โ€ข On-site

$225K/yr

Other

PTO

Re-posted 29 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.ย  We strongly encourage you to focus on applying to a single role that best matches your skills and interests.ย  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