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Junior Machine Learning Compiler Engineer Jobs in Wisconsin

Senior AI Engineer

Madison, WI · On-site

$105.30K - $144.60K/yr

You will work closely with AI leadership while providing day-to-day technical guidance to junior team members. This position blends applied machine learning, software engineering, cloud architecture ...

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$102.70K - $141K/yr

... machine learning applications. Responsibilities : • Work with clients to design, develop, and ... coach junior members on technical best practices and inspire professional development ...

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Senior AI Engineer

Green Bay, WI · On-site

$101.60K - $139.60K/yr

JOB RESPONSIBILITIES Generative AI and Machine Learning Development: * Implement and integrate ... Share knowledge about AI/ML best practices with teammates and mentor junior engineers interested in ...

Senior AI Engineer - SFL Scientific

Milwaukee, WI

$103K - $141.40K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

Senior AI Engineer

Green Bay, WI · On-site

$101.60K - $139.60K/yr

JOB RESPONSIBILITIES Generative AI and Machine Learning Development: * Implement and integrate ... Share knowledge about AI/ML best practices with teammates and mentor junior engineers interested in ...

1st Shift VTL Machinist

Appleton, WI · On-site

$21.50 - $29/hr

At A to Z Machine , we're not just cutting metal-we're shaping careers. As an employee-owned ... Strong knowledge of G-code and CNC programming * Ability to work independently and solve complex ...

The ideal candidate will have a strong background in machine learning, natural language processing ... Experience in prompt engineering, model fine-tuning, and API integration. * Solid background in ...

Develop and implement statistical and machine learning models * Fine-tune, optimize and ensure the ... Mentor and guide junior data scientists, providing technical expertise and fostering a culture of ...

Collaborate closely with business stakeholders, data scientists, machine learning engineers, and ... software engineers to ensure smooth integration of machine learning models into production systems.

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Junior Machine Learning Compiler Engineer information

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 the most commonly searched types of Machine Learning Compiler Engineer jobs in Wisconsin? The most popular types of Machine Learning Compiler Engineer jobs in Wisconsin are:
What are popular job titles related to Junior Machine Learning Compiler Engineer jobs in Wisconsin? For Junior Machine Learning Compiler Engineer jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Junior Machine Learning Compiler Engineer jobs? Cities in Wisconsin with the most Junior Machine Learning Compiler Engineer job openings:

Senior AI Engineer

Clifton Larson Allen

Madison, WI • On-site

$105.30K - $144.60K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.

CLA is currently seeking a Senior AI Engineer to join our growing CLA Digital - Data and Automation Team. The Senior AI Engineer will lead the design and implementation of production-grade AI solutions across machine learning, optimization, and generative AI. This role is ideal for someone who can translate business problems into scalable, reliable technical solutions that perform in real-world environments.

You will work closely with AI leadership while providing day-to-day technical guidance to junior team members. This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI involves far more than model development-it includes evaluation, observability, integration, governance, and operational excellence.

About the role:

AI Solution Development & Architecture

  • Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications
  • Design end-to-end architectures including data pipelines, APIs, model services, orchestration layers, and monitoring systems
  • Build and deploy AI workflows within Azure and Databricks environments
  • Develop robust evaluation frameworks for both ML models and LLM-based systems
  • Design and implement AI applications with strong grounding, safety, evaluation, and cost controls
  • Build AI workflows including tool integration, memory systems, and orchestration logic
  • Implement model routing, fallback strategies, and guardrails
  • Develop context and memory systems (retrieval, summarization, session continuity)
Evaluation, Safety & Reliability
  • Establish robust evaluation frameworks for ML and LLM systems
  • Define and monitor:
    • Task success metrics and regression testing
    • Hallucination and grounding performance
    • Safety risks (prompt injection, data leakage)
  • Implement observability practices including logging, tracing, and monitoring
  • Ensure system reliability through testing, deployment standards, and incident readiness
Technical Leadership
  • Translate ambiguous business needs into clear technical designs and delivery plans
  • Provide mentorship and technical oversight to junior engineers
  • Lead architecture reviews, code reviews, and technical design discussions
  • Establish engineering standards across testing, CI/CD, deployment, and monitoring
Cross-Functional Collaboration
  • Partner with product, engineering, security, and business stakeholders
  • Support solution design, feasibility assessments, and delivery planning
  • Contribute to proposals, technical narratives, and client-facing engagements
Core Responsibilities
  • Own major technical workstreams for AI delivery from design through deployment
  • Build scalable data and model pipelines for batch and real-time use cases
  • Lead development of LLM-based applications with strong grounding, evaluation, safety, and cost controls
  • Implement classical AI and advanced analytics approaches including forecasting, anomaly detection, optimization, recommendation, and decision support
  • Define and implement MLOps and LLMOps standards including versioning, deployment, monitoring, and rollback strategies
  • Design secure and supportable integrations across enterprise systems, APIs, and data platforms
  • Evaluate tradeoffs across tools, frameworks, and architecture choices in Azure and Databricks
  • Troubleshoot complex issues in production environments across data, infrastructure, and application layers
  • Drive technical quality and ensure solutions are maintainable, scalable, and aligned to client needs
  • Support business development by contributing to solution framing, estimates, and technical narratives

What you will need:

  • 2 years of relevant experience required
  • 5-7 years of experience in AI engineering, machine learning, or software engineering preferred
  • Strong proficiency in Python and production-grade development practices preferred
  • Proven experience deploying ML/AI systems into production environments preferred
  • Experience designing APIs, pipelines, and service-oriented architectures preferred
  • Strong understanding of model evaluation, experimentation, and performance tradeoffs preferred
  • Ability to work independently and mentor junior team members
  • Strong communication skills across technical and non-technical audiences

Our Perks:

Flexible PTO (designed to offer flexible time away for you!)

Up to 12 weeks paid parental leave

Paid Volunteer Time Off

Mental health coverage

Quarterly Wellness stipend

Fertility benefits

Complete list of benefits here

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Wellness at CLA

To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k and much more.

To view a complete list of benefits click here.