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Junior Machine Learning Compiler Engineer Jobs in Summit, IL

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and ...

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying ... Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and ...

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with ...

Machine Learning Engineer

Chicago, IL · On-site

$175K - $250K/yr

Machine Learning Engineer Chicago, United States; Hong Kong, Hong Kong; Sydney, Australia As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and ...

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of ...

Machine Learning Engineer

Chicago, IL · On-site

$175K - $250K/yr

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with ...

Machine Learning Engineer

Chicago, IL · On-site

$175K - $250K/yr

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with ...

Machine Learning Engineer Location: San Jose, CA/Chicago, IL Duration: 18 months contract with a possible extension What You'll Do • Redesign and optimize PayPal's MLOps and decision platform for ...

Machine Learning Engineer

Chicago, IL · On-site

$160K - $220K/yr

Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers our platform. This is a zero-to-one role. You will be the first dedicated ML hire and will own how ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

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Junior Machine Learning Compiler Engineer information

See Summit, IL salary details

$33.6K

$72.1K

$109.9K

How much do junior machine learning compiler engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for junior machine learning compiler engineer in Summit, IL is $72,088.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,700.00 and $80,300.00 per year, depending on experience, location, and employer.

What are typical projects and responsibilities for a Junior Machine Learning Compiler Engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

What does a Junior Machine Learning Compiler Engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Compiler Engineer, and why are they important?

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

What is the difference between Junior Machine Learning Compiler Engineer vs Data Scientist?

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

What are popular job titles related to Junior Machine Learning Compiler Engineer jobs in Summit, IL? For Junior Machine Learning Compiler Engineer jobs in Summit, IL, the most frequently searched job titles are:
What cities near Summit, IL are hiring for Junior Machine Learning Compiler Engineer jobs? Cities near Summit, IL with the most Junior Machine Learning Compiler Engineer job openings:
Infographic showing various Junior Machine Learning Compiler Engineer job openings in Summit, IL as of June 2026, with employment types broken down into 84% Full Time, 5% Part Time, 7% Contract, and 4% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $72,088 per year, or $34.7 per hour.

Hardware Machine Learning Engineer

IMC

Chicago, IL

$127K - $167K/yr

Other

Posted 12 days ago


Job description

We are deploying machine learning directly onto custom hardware - and we want you to help drive it from the ground up. This is an initiative where you'll have the rare opportunity to architect solutions from scratch, influence technical research direction, and see your work drive real impact in one of the most demanding computing environments in the world.

We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can fix it - there's no vendor to wait on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the boundaries of what's computationally possible, this role is for you. We're looking for researchers and experienced engineers from any background. Trading experience is a bonus, not a prerequisite.

Your Core Responsibilities

  • Architect and co-design ML models with traders, quant researchers, and software engineers, treating hardware constraints (latency budgets, resource limits, numerical precision) as first-class design inputs
  • Shape our custom hardware roadmap by translating ML model requirements into concrete architectural decisions
  • Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production
  • 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

Your Skills and Experience

  • 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, C++, 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

Nice to Have

  • Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and optimizing models for hardware targets
  • Background in latency-sensitive or resource-constrained systems including high-frequency trading, particle physics data acquisition, real-time signal processing, or similar domains
  • Familiarity with functional verification methodologies (for example SystemVerilog, UVM, Cocotb)
  • Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through industry or research experience