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Senior Embedded Machine Learning Jobs in Michigan

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain ... senior guidance * Excellent understanding of model evaluation techniques, feature engineering ...

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. * 10+ years in IT ...

Senior Software Engineer I

Ann Arbor, MI · On-site

$123K - $161K/yr

... team, the Sr Software Engineer I at New Eagle is responsible is responsible for designing ... Automotive (broadR reach) ethernet for networking embedded systems. Fieldbus protocols for machine ...

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Showing results 1-20

Senior Embedded Machine Learning information

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are some common challenges faced by Senior Embedded Machine Learning Engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

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

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What does a Senior Embedded Machine Learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.
What are the most commonly searched types of Embedded Machine Learning jobs in Michigan? The most popular types of Embedded Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Senior Embedded Machine Learning jobs? Cities in Michigan with the most Senior Embedded Machine Learning job openings:
Senior Machine Learning Test Engineer

Senior Machine Learning Test Engineer

Autodesk

Novi, MI • On-site, Remote

$103K - $134K/yr

Full-time

Posted 25 days ago


Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

6th of 186 rated software companies


Job description

Job Requisition ID #

26WD98377

Senior Machine Learning Test Engineer

Location: United States East Coast

Position Overview

As a Senior Machine Learning Test Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning developers and developers, and software developers and developers to define and uphold quality standards for ML systems. You are a quality-focused developer who is passionate about reliable, repeatable evaluation of ML models and data. Your skills span test strategy, automation, and a little MLOps, with a strong software engineering base. You are excited to collaborate across research and product to ship ML capabilities with clear quality gates. You are comfortable working at the intersection of research and product and are competent in using Autodesk CAD software.

Reporting Structure: You will report to an Engineering Manager in Research Enablement.

Location: United States, East Coast Time Zone.

We are a global team, located in London, San Francisco, Toronto, and remotely. Autodesk is a hybrid-first company, allowing workers to work remotly, in an office, or a mix of both.

Responsibilities

  • Define ML quality strategy and acceptance criteria across data, model, and system levels

  • Design and maintain model evaluation suites, metrics, and test datasets

  • Evaluating CAD RL model outputs for geometric validity or policy stability

  • Defining structured rubrics that translate qualitative findings into measurable evaluation gates

  • Testing ML Models from product side

  • API Testing

  • Automate ML QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins)

  • Create and maintain test harnesses for ML services and APIs

  • Mentor teams on ML QA best practices and consistent evaluation standards

  • Build quality gates for training and deployment pipelines (e.g., regression checks, drift detection)

  • Contribute to multi-team projects and codebases, ensuring code quality and consistency

  • Participate in code reviews and provide constructive feedback to peers

  • Document and present findings and ideas across the company

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, or equivalent experience

  • 7+ years of professional experience in software engineering or QA for ML/AI systems

  • Strong programming skills in Python, with experience in test automation

  • Familiarity with popular CAD environments tooling

  • Proficient in Automation and UAT test suite/framework

  • Experience designing QA frameworks or platforms used by multiple teams

  • Excellent problem-solving skills and attention to detail

  • Strong communication and collaboration skills

  • Understanding of software architecture and design patterns

  • Ability to work in an agile development environment

Preferred Qualifications

  • Experience with data validation tooling (e.g., Great Expectations) or labeling workflows

  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow)

  • Experience with CI/CD tools and processes

  • Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)

  • Familiarity with MLOps practices (model monitoring, drift, deployment checks)

  • Experience with ML evaluation methods, metrics, and benchmarking

  • Passion for learning new technologies and improving existing systems

  • Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform)

  • Experience testing ML services in production environments

  • Knowledge of experiment tracking tools (e.g., Comet, MLflow, Weights & Biases)

The Ideal Candidate

  • You demonstrate initiative to provide solutions and to learn and develop new technologies

  • Comfortable building QA systems from scratch and writing maintainable automation

  • You enjoy learning and collaborating across global locations

  • You are comfortable working in newly forming ambiguous areas

  • You are comfortable building scalable and maintainable systems that will be relied on by others

  • You can communicate well with others

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers.

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About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982