1

Embedded Machine Learning Engineer Jobs in Minnesota

Principal Machine Learning Engineer Our client is a digital consumer product. They're building social features using LLMs and Machine Learning to add to user experience. We're looking for a Principal ...

Job Requisition ID # 26WD97132 26WD97132, Pr incipal Machine Learning Engineer, ML Platform and Systems Architecture French translation to follow!/Traduction francaise a suivre! Position Overview The ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

We're looking for a Principal Machine Learning Engineer to build AI features for the family. Qualifications: * A confident craftsperson who possesses problem-solving tools and can discuss multiple ...

AI Center of Excellence as a Machine Learning Engineer Consultant! In this exciting role, you?ll collaborate with talented experts to build innovative solutions that address our company?s evolving ...

We're looking for a Principal Machine Learning Engineer to build AI features for the family. Qualifications: * A confident craftsperson who possesses problem-solving tools and can discuss multiple ...

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

AI Engineer

Saint Paul, MN · On-site

$110K - $130K/yr

... machine learning algorithms used in cardiac remote monitoring. This position will work alongside and collaborate closely with engineers with expertise in signal processing, embedded systems, cloud ...

Embedded Engineer, Senior

Minneapolis, MN

$129.40K - $169.60K/yr

Senior Embedded/Firmware Engineer Nordson Test & Inspection, a global leader in X-Ray & Test ... areas of 3D machine vision and semiconductor process measurement. Our sensors are deployed in ...

Embedded Engineer, Senior

Hills, MN · On-site

$119.40K - $156.50K/yr

... areas of 3D machine vision and semiconductor process measurement. Our sensors are deployed in ... A Senior Embedded/Firmware Engineer is responsible for the implementation of firmware for Nordson ...

Embedded Engineer, Senior

Minneapolis, MN

$129.40K - $169.60K/yr

... areas of 3D machine vision and semiconductor process measurement. Our sensors are deployed in ... A Senior Embedded/Firmware Engineer is responsible for the implementation of firmware for Nordson ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

Machine Learning Engineer Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve ...

next page

Showing results 1-20

Embedded Machine Learning Engineer information

See Minnesota salary details

$68.6K

$150.2K

$170.4K

How much do embedded machine learning engineer jobs pay per year?

As of Jun 3, 2026, the average yearly pay for embedded machine learning engineer in Minnesota is $150,226.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,800.00 and $169,400.00 per year, depending on experience, location, and employer.

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

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Minnesota? For Embedded Machine Learning Engineer jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Embedded Machine Learning Engineer jobs? Cities in Minnesota with the most Embedded Machine Learning Engineer job openings:

Principal AI / ML Engineer

NxT Level

Minneapolis, MN • On-site, Remote

Other

Medical, Retirement, PTO

Posted 9 days ago


Job description

Principal Machine Learning Engineer

Our client is a digital consumer product. They're building social features using LLMs and Machine Learning to add to user experience. We're looking for a Principal Machine Learning Engineer to build AI features for the family.

Qualifications
  • A confident craftsperson who possesses problem-solving tools and can discuss multiple approaches while preferring the best approach given the constraints.
  • A scientific artist and artistic scientist who can navigate complexity and bring clarity to intricate problems while appreciating simplicity as the highest sophistication.
  • A pragmatic optimizer who identifies the need for change, articulates it, and drives incremental improvements toward ambitious goals.
  • An advocate for team collaboration and open communication.
  • Possesses comprehensive knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and advanced NLP techniques.
  • Significant experience in AI/ML engineering with a strong data science background.
  • Demonstrated ability in designing and training LLMs.
  • Expertise in Databricks/Apache Spark for large-scale data processing in AI/ML applications.
  • Proficiency with AWS Bedrock and Comprehend.
  • Demonstrated leadership in AI/ML solutions in a commercial environment.
  • Proficiency with programming languages such as R, Python, and Java, with a focus on data exploration and processing.
  • Proven ability to lead and inspire teams of senior engineers and data scientists.
  • Effective individual contributor within a collaborative team environment.
  • Strong analytical, problem-solving, and communication skills.
Responsibilities
  • Collaborate with the Data team to transform Data Lakehouse potential into actionable insights and services that enhance user experiences.
  • Shape AI/ML strategies, particularly in LLMs, to drive business outcomes and establish data science principles.
  • Implement technologies in AWS and Databricks for handling and processing large datasets for advanced language model training.
  • Lead data science practices, including model selection and training methodology.
  • Build, train, manage, and host LLMs using Data Lakehouse data.
  • Optimize AI system performance through testing and tuning, leveraging data science and Databricks methodologies.
  • Ensure ethical standards and data privacy compliance in AI solutions.
  • Provide specialized AI/ML expertise to guide the development and optimization of AI features.
  • Stay updated on the latest AI/ML and data science trends, especially in LLMs and AWS, Databricks/Apache Spark technology.
Benefits
  • Full Medical Coverage: OFW covers 100% of premiums for employees and their families.
  • 401k: Up to a 4% match with immediate vesting.
  • 12 weeks of paid leave for all new parents.
  • Learning & Development stipend for employees.
  • Supportive and flexible working environment, allowing remote work from anywhere.