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Remote Machine Learning Compiler Engineer Jobs in Michigan

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

... machine learning models and algorithms to solve complex business problems. * Collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to identify ...

Senior AI Engineer

Grand Rapids, MI · On-site +1

$100K - $137K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

Knowledge of machine learning algorithms, data analysis and programming. * Experience working in a ... OneStream is an Equal Opportunity Employer. #LI-REMOTE #LI-JP1

New

Data Scientist

Dearborn, MI · On-site +1

$128K - $186K/yr

... managed machine learning services. 3. A/B testing design, implementation, and analysis, and ... Engineering, Computer Applications or a related field and 5 years of experience in the job offered ...

$104K - $142K/yr

Experiences/Education - Required Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field, or equivalent practical experience ...

Data Science Tutor

Detroit, MI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Kalamazoo, MI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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Remote Machine Learning Compiler Engineer information

How does a Remote Machine Learning Compiler Engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a Remote Machine Learning Compiler Engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

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

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

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

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Michigan? The most popular types of Machine Learning Compiler Engineer jobs in Michigan are:
What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Michigan? For Remote Machine Learning Compiler Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Compiler Engineer jobs in Michigan look for? The top searched job categories for Remote Machine Learning Compiler Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Machine Learning Compiler Engineer jobs? Cities in Michigan with the most Remote Machine Learning Compiler Engineer job openings:
Data Scientist - Materials R&D - Remote-Travel

Data Scientist - Materials R&D - Remote-Travel

Intertape Polymer Group (IPG)

Marysville, MI • On-site, Remote

Full-time

Re-posted 25 days ago


Intertape Polymer Group rating

6.8

Company rating: 6.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

77th of 112 rated packaging manufacturers


Job description

Join the IPG Team!

Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutions—we are a community that values safety, people, passion, integrity, performance, and teamwork. From tapes and films to packaging and protective products, as well as engineered coated materials and advanced packaging machinery, we develop innovative solutions that protect the world. Now, we are expanding our global team and looking for talented individuals like you!

This position can be based out of Marysville, MI, or work remotely with some travel as needed.

Title:                                 Senior Data Scientist

Department:                    Research and Development

Immediate Supervisor:   R&D Vice President

Status:                              Exempt Salaried    

 

Position Purpose:            The Senior Data Scientist will support R&D efforts in bio-polymers and sustainable materials and focusing on applying advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles.

  Principle Accountabilities
  • Partner with polymer scientists, chemists, and engineers to support bio‑polymer research and development using data-driven methods
  • Analyze and model experimental, formulation, and process data to identify structure–property–process relationships
  • Develop predictive models to support:
    • Material performance and property optimization
    • Formulation design and screening
    • Scale‑up and process optimization
  • Design and analyze experiments (DOE) to maximize learning efficiency and reduce development timelines
  • Build and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysis
  • Apply machine learning techniques (e.g., regression, classification, clustering, time-series modeling) to complex scientific datasets
  • Collaborate with data engineering and IT teams to enable scalable data infrastructure for R&D
  • Communicate insights, tradeoffs, and recommendations clearly to technical and non-technical stakeholders
  • Understanding of data visualization best practices
  • Experience working with batch or streaming data processes a plus
  • Contribute to data dictionaries and process flow diagrams for complex data solutions
  • Mentor junior data scientists or technical staff and contribute to data science best practices within R&D
  • Stay current with advances in materials informatics, polymer modeling, and applied AI in scientific research
Essential Skills and Experience 
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Master’s or PhD preferred
  • 10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, preferred
  • Strong proficiency in Python and/or R for data analysis and modeling
  • Solid experience with SQL and working with structured and semi-structured datasets
  • Strong foundation in statistics, experimental design, and multivariate analysis
  • Demonstrated experience applying machine learning to real-world, noisy scientific or experimental data
  • Ability to work effectively in a cross-functional R&D environment
  • Strong communication skills with the ability to translate complex analyses into actionable insights
  • Familiarity with bio‑polymers, sustainable materials, or polymer processing, preferred
  • Experience with DOE software, laboratory data management systems (LIMS), or scientific databases, preferred
  • Experience deploying models to support R&D decision-making or manufacturing scale-up, preferred
  • Familiarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools, preferred
  • Prior experience mentoring or leading technical projects, preferred

Why Choose IPG?

At IPG, you will find more than just a job—you will find a place where your success is our success. We pride ourselves on a culture built around strong relationships, where every team member plays a crucial role in our growth. Whether it is through cross-department collaboration, continuous training, or sustainability-driven initiatives, we create an environment where you can thrive.

Our commitment to sustainability influences everything we do, from designing eco-friendly products to minimizing waste in our production processes. We are dedicated to building a greener future while providing safe, supportive workplaces for our people.

With over 40 years of industry expertise and a proven track record of growth and innovation, IPG offers a stable, secure environment where you can flourish!

We offer competitive pay, extensive benefits that support you and your family, and exciting career development opportunities. Whether you are looking to enhance your skills or advance your career, we offer ongoing training and the support you need to succeed. Think big, dream bigger, and make an impact with IPG.

You belong here. Join us today!


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