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Junior Machine Learning Compiler Engineer Jobs in Wheaton, IL

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems. The ...

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems. The ...

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems. The ...

Hardware Machine Learning Engineer

Chicago, IL

$127.20K - $167.90K/yr

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 ...

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

$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 ...

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users. As a Senior ...

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Junior Machine Learning Compiler Engineer information

See Wheaton, IL salary details

$32.4K

$69.4K

$105.8K

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

As of May 29, 2026, the average yearly pay for junior machine learning compiler engineer in Wheaton, IL is $69,395.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,900.00 and $77,300.00 per year, depending on experience, location, and employer.

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 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 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 Wheaton, IL? For Junior Machine Learning Compiler Engineer jobs in Wheaton, IL, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Compiler Engineer jobs in Wheaton, IL look for? The top searched job categories for Junior Machine Learning Compiler Engineer jobs in Wheaton, IL are:
What cities near Wheaton, IL are hiring for Junior Machine Learning Compiler Engineer jobs? Cities near Wheaton, IL with the most Junior Machine Learning Compiler Engineer job openings:

Machine Learning Engineer

Ontrac Solutions LLC

Chicago, IL • On-site

$70 - $90/hr

Contractor

Posted yesterday


Job description

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation engagement for one of our clients.
This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems.
The selected engineers will work under the direct guidance of a Staff ML Architect and will focus heavily on daily MLOps execution, pipeline maintenance, model reliability, and production support for a high-traffic digital platform.
Required Credentials
  • 2+ years of experience in machine learning engineering, data engineering, software engineering, or a related technical role.
  • Hands-on experience supporting production or near-production ML systems.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or equivalent practical experience.
Required Qualifications
  • Solid hands-on experience with the GCP ecosystem, particularly Vertex AI components such as Workbench, Pipelines, and Model Registry.
  • Proficiency with modern ML frameworks, including PyTorch or similar technologies.
  • Experience with containerization tools, especially Docker, for automated builds and deployments.
  • Practical experience managing data processing workflows using Apache Spark and Airflow.
  • Understanding of MLOps best practices, including model deployment, monitoring, training workflows, inference support, and pipeline reliability.
  • Familiarity with real-time model serving and infrastructure tools such as Triton Inference Server and Terraform is highly preferred.
  • Strong problem-solving skills with the ability to troubleshoot, maintain, and optimize ML pipelines in a production environment.
  • Collaborative mindset with the ability to execute technical tasks reliably under the guidance of a senior architect.
Key Responsibilities
  • Support the design, deployment, monitoring, and maintenance of machine learning models in a high-traffic production environment.
  • Maintain, troubleshoot, and optimize end-to-end ML pipelines from raw data ingestion through offline and online model evaluation.
  • Execute daily MLOps tasks, including model training, inference support, pipeline monitoring, and deployment maintenance.
  • Work with tools such as GCP, Vertex AI, Spark, Airflow, Docker, PyTorch, and related MLOps technologies.
  • Build and manage automated containerized deployments to support continuous model operations.
  • Partner closely with the Staff ML Architect and other ML Engineers to ensure models are reliable, scalable, and production-ready.
  • Help identify and resolve performance, reliability, and scalability issues across ML workflows and infrastructure.
Preferred Qualifications
  • Prior experience supporting high-traffic digital platforms or consumer-facing products.
  • Experience with Triton Inference Server, Terraform, or similar infrastructure and real-time serving tools.
  • Experience working in staff augmentation, consulting, or fast-moving client-facing environments.
  • Strong interest in building reliable, production-grade ML systems rather than only experimental or research-focused models.
About Ontrac Solutions
Ontrac Solutions is a strategic consulting and technology solutions firm helping companies Innovate. Create. Elevate. through digital product consulting, cloud solutions, AI-based data solutions, and staff augmentation.
We partner with clients to bring the right technical expertise, execution support, and strategic guidance to complex business and technology initiatives.