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Internship Full Stack Machine Learning Engineer Jobs in Chicago, IL

IMC

Principal Machine Learning Engineer

Chicago, IL

$200K - $250K/yr

We're looking for a Principal Machine Learning Engineer to help shape the next phase of our ... Comfort working across the ML stack from data pipelines to training infrastructure to serving ...

Reyes Coca-Cola Bottling

Machine Learning Engineer

Niles, IL · On-site

$53 - $72.75/hr

Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML ...

Reyes Coca-Cola Bottling

Machine Learning Engineer

Niles, IL · On-site

$53 - $72.75/hr

Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML ...

Indeed

Senior Machine Learning Engineer

Chicago, IL

$107K - $147K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... stack that powers Pictor's virtual staining. The ideal candidate will have deep expertise in ...

Globant

Full Stack Engineer

Chicago, IL · On-site

We are looking for a smart and passionate Full stack engineer to join our team. * You will be ... Other AWS services not mentioned above (Hosted DBs, SQS, Machine Learning) * Terraform Additional ...

The Hartford

AI Machine Learning Engineer

Chicago, IL · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... Our products are delivered with a full monitoring solution to ensure our products continue to ...

UST Inc

AWS Machine Learning Engineer

Chicago, IL

$72K - $108K/yr

Role description AWS Machine Learning Engineer ML Engineer I Who We Are: Born digital, UST transforms lives through the power of technology. We walk alongside our clients and partners, embedding ...

SynergisticIT

Junior Data Engineer

Evanston, IL

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

IMC Inc

Hardware Machine Learning Engineer

Chicago, IL

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying machine learning directly onto custom hardware - and we want you to help drive it from the ground ...

York Solutions, LLC

Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

... engineers; comfortable making architectural decisions and rallying others around them. Preferred Qualifications Background in signal processing, computer vision, or multimodal learning. Prior ...

Grapefruit Health

Full Stack Engineer

Chicago, IL · On-site +1

$100K - $120K/yr

The Role We are looking for a Full Stack Engineer who thrives on ownership and loves building ... Stay curious and keep learning * Communicate clearly across technical and non-technical teams

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All JobsInternship Full Stack Machine Learning Engineer JobsInternship Full Stack Machine Learning Engineer Jobs in Chicago, IL

Internship Full Stack Machine Learning Engineer information

See Chicago, IL salary details

$45.8K

$138.8K

$196.2K

How much do internship full stack machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for internship full stack machine learning engineer in Chicago, IL is $138,833.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,300.00 and $162,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Full Stack Machine Learning Engineer, and why are they important?

To succeed as an Internship Full Stack Machine Learning Engineer, you need a solid understanding of programming (Python, JavaScript), basic machine learning concepts, and foundational knowledge in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, web development tools (React, Node.js), and version control systems like Git is typically expected. Strong problem-solving abilities, collaboration skills, and a willingness to learn set exceptional interns apart. These skills enable interns to contribute effectively to both model development and deployment, bridging the gap between data science and software engineering in real-world applications.

What is an Internship Full Stack Machine Learning Engineer?

An Internship Full Stack Machine Learning Engineer is a student or early-career professional who supports both the development of machine learning models and the integration of these models into full-stack applications. This role typically involves working on data preprocessing, building and training machine learning algorithms, and deploying these models within web or mobile applications. Interns in this field gain experience in both backend and frontend technologies, as well as in machine learning frameworks and tools. The position is ideal for those seeking hands-on experience in applying AI solutions within real-world products.

What types of projects and responsibilities can I expect as an Internship Full Stack Machine Learning Engineer?

As an Internship Full Stack Machine Learning Engineer, you can expect to work on end-to-end machine learning projects that involve both model development and integration into web or cloud applications. This may include tasks like cleaning and preparing datasets, building and testing machine learning models, developing APIs to serve predictions, and collaborating with front-end developers to deliver user-facing features. Interns often work closely with data scientists, software engineers, and product managers, gaining exposure to the full development lifecycle. These experiences help build both technical and teamwork skills, laying a strong foundation for a future career in the field.

What is the difference between Internship Full Stack Machine Learning Engineer vs Software Developer Intern?

AspectInternship Full Stack Machine Learning EngineerSoftware Developer Intern
Required SkillsKnowledge of machine learning, programming (Python, JavaScript), full stack development, data handlingProficiency in programming languages (Java, Python, JavaScript), software development, basic algorithms
Work EnvironmentCollaborates on ML models, data pipelines, backend and frontend developmentFocuses on application development, coding, debugging, and testing
Industry UsageUsed in AI-driven companies, tech startups, data science teamsCommon in software firms, app development companies, tech startups

The Internship Full Stack Machine Learning Engineer role emphasizes working with machine learning models and data-driven applications, combining full stack development skills with AI expertise. In contrast, a Software Developer Intern focuses more on traditional software development tasks like coding and debugging. Both roles are valuable entry points in tech, but they target different skill sets and project types.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Chicago, IL? The most popular types of Full Stack Machine Learning Engineer jobs in Chicago, IL are:
What are popular job titles related to Internship Full Stack Machine Learning Engineer jobs in Chicago, IL? For Internship Full Stack Machine Learning Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Internship Full Stack Machine Learning Engineer jobs in Chicago, IL look for? The top searched job categories for Internship Full Stack Machine Learning Engineer jobs in Chicago, IL are:
Internship Full Stack Machine Learning Engineer jobs near you

Principal Machine Learning Engineer

IMC

Chicago, IL

$200K - $250K/yr

Other

PTO

Posted 10 days ago

Job description

At IMC, we believe technology is the foundation of our competitive edge - and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. Now we're expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll work alongside researchers and technologists to design the systems that power experimentation, training, and deployment of ML models - and help set the direction for how machine learning is done at IMC as we scale. If you've built ML infrastructure at scale elsewhere and are looking for a role where your ideas will genuinely help shape our firm's future - we'd love to hear from you.
Your Core Responsibilities:
  • Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster
  • Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines
  • Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading
  • Work with researchers to adapt and deploy modern architectures - transformers, state-space models, temporal convolutions, graph neural networks - to noisy, high-frequency financial data. Explore techniques like self-supervised pretraining, representation learning, and cross-sectional modelling where they offer genuine edge
  • Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment
  • Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work
  • Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work - whether that's new architectures, training techniques, or tooling

Your Skills and Experience:
  • 8+ years of experience building ML platforms or infrastructure at a leading tech company, research lab, or quantitative firm
  • A track record of designing and owning large-scale training and inference systems - not just contributing, but architecting
  • Deep proficiency in Python, with strong experience in either CUDA or C++
  • Hands-on expertise with modern deep learning frameworks (PyTorch, TensorFlow, or JAX) and practical experience implementing architectures like transformers, attention mechanisms, or sequence models
  • Strong foundation in deep learning fundamentals: optimization, regularization, loss design, and the trade-offs that matter when training at scale
  • Experience with distributed training at scale (Horovod, NCCL) and GPU optimization (cuDNN, TensorRT)
  • History of deploying models to production with strong observability, reproducibility, and monitoring practices
  • Comfort working across the ML stack from data pipelines to training infrastructure to serving systems

Why This Role:
  • Build, don't inherit - You'll make foundational technology choices in a platform that's still being defined, not maintain someone else's legacy.
  • Real investment, real backing - This is a strategic priority with resources behind it, not a side experiment.
  • Direct impact on trading - Your infrastructure will power models that make real trading decisions in competitive global markets.
  • Global scope - Work with teams across New York, Chicago, Amsterdam, London, Sydney, Hong Kong and beyond; define practices that can scale worldwide.
  • Ideas over titles - IMC's culture values clarity, rigor, and collaboration. The best ideas win, regardless of where they come from.
  • Tight coupling with research - You won't be building in isolation. Researchers and engineers work side-by-side, iterating together.

#LI-DNP
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.
Salary Range
$200,000-$250,000 USD
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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