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Hourly Embedded Machine Learning Jobs in Minneapolis, MN

Onsights

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

As a Senior Machine Learning Engineer, you will design, develop, test, document, deploy, and ... g., embedded systems, microcontrollers) • Prior experience supporting U.S. Department of War ...

VivaQuant, Inc.

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 ...

System One

Data Scientist

Minneapolis, MN · On-site

... machine learning models. In this role, you will bridge the gap between traditional data science and software engineering by writing clean, modular Python code to build robust AI capabilities embedded ...

System One Holdings, LLC

Data Scientist

Minneapolis, MN · On-site

... machine learning models. In this role, you will bridge the gap between traditional data science and software engineering by writing clean, modular Python code to build robust AI capabilities embedded ...

System One

Data Scientist

Minneapolis, MN · On-site

... machine learning models. In this role, you will bridge the gap between traditional data science and software engineering by writing clean, modular Python code to build robust AI capabilities embedded ...

Grace Church

Chaska NXT Intern

Chaska, MN · On-site

$20/hr

Grace Church - Chaska Part-time - 10 hours/week Pay: $20.00/hour Hourly - Non-Exempt KEY DUTIES AND ... Read, discuss, and participate in required learning assignments with supervisor. Chaska Worship ...

Tactile Medical

Data Scientist

Minneapolis, MN · On-site

$100K - $150K/yr

... machine learning and statistical methodologies • Translating validated models into forward ... Below is the starting salary or hourly range for this position, although offers may differ based on ...

Minco Products

Machinist

Fridley, MN · On-site

$19 - $40/hr

Applying machine shop theory and practices * Reading blueprints, sketches, drawings, manuals, and ... Find out why you would love working at Minco by learning more about our company culture and the ...

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All JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Minneapolis, MN

Hourly Embedded Machine Learning information

See Minneapolis, MN salary details

$73.1K

$160.1K

$181.6K

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

As of Jul 27, 2026, the average yearly pay for hourly embedded machine learning in Minneapolis, MN is $160,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,300.00 and $180,600.00 per year, depending on experience, location, and employer.

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

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

How does an Hourly Embedded Machine Learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What is an Hourly Embedded Machine Learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What are the most commonly searched types of Embedded Machine Learning jobs in Minneapolis, MN? The most popular types of Embedded Machine Learning jobs in Minneapolis, MN are:
What are popular job titles related to Hourly Embedded Machine Learning jobs in Minneapolis, MN? For Hourly Embedded Machine Learning jobs in Minneapolis, MN, the most frequently searched job titles are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Minneapolis, MN look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Minneapolis, MN are:
What cities near Minneapolis, MN are hiring for Hourly Embedded Machine Learning jobs? Cities near Minneapolis, MN with the most Hourly Embedded Machine Learning job openings:
Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Minneapolis, MN as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $160,102 per year, or $77 per hour.

Senior Machine Learning Engineer

Onsights

Minneapolis, MN • On-site

$109K - $149K/yr

Full-time

Posted 10 days ago

Job description

Job Summary:
Anno.ai is a mission-focused defense technology startup dedicated to accelerating the safe and effective development of next-generation autonomous systems. As a Senior Machine Learning Engineer, you will design, develop, test, document, deploy, and maintain production machine learning and statistical modeled software to automate processes and streamline customer mission operations.
Responsibilities:
• Operationalize machine learning models by building and maintaining robust, scalable pipelines for training, evaluation, deployment, and lifecycle management across cloud, on-prem, and edge compute environments
• Work closely with autonomy researchers, software engineers, systems teams, and field operators to translate mission requirements into deployable ML capabilities
• Implement automated CI/CD workflows tailored to ML systems, ensuring repeatable experiments, reliable packaging, and continuous delivery of both up to date models and associated data pipelines
• Manage ML runtime infrastructure using containerization and orchestration frameworks (e.g., Docker, Kubernetes) and incorporating model serving platforms (e.g., Seldon, KServe, BentoML)
• Develop monitoring systems to track model health, performance, data drift, system utilization, and mission relevance using tools such as Prometheus, Grafana, and ELK/EFK stacks
• Ensure ML deployments meet defense, customer, and platform security requirements, with emphasis on data integrity, traceability, and operational reliability
• Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, extensibility, scalability, and deployment speed of ML systems
Qualifications:
Required:
• Bachelor's degree in Computer Science, Electrical Engineering, Data Science, or a related technical field (Master's preferred)
• 5+ years of professional experience in software engineering, machine learning engineering, MLOps, or related roles
• Experience operationalizing ML systems at production scale, including model training, versioning, packaging, deployment, and monitoring
• Strong proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow)
• Hands-on experience with MLOps frameworks and workflow tooling (e.g., MLflow, Kubeflow, Airflow, DVC, BentoML)
• Experience deploying containerized ML services using Docker and orchestrating workloads using Kubernetes (including air-gapped or constrained deployments)
• Understanding of CI/CD workflows and DevOps practices applied to ML systems (e.g., Git, Code Review, Metrics Evaluation)
• Familiarity with monitoring, observability, and logging platforms (e.g., Prometheus, Grafana, ELK/EFK)
• Ability to obtain and maintain U.S. Government security clearance (U.S. Citizenship required)
• Ability to travel up to 20%
Preferred:
• Experience with deploying models and associated runtimes to Edged Devices
• Experience optimizing models for memory and CPU constrained systems (e.g., embedded systems, microcontrollers)
• Prior experience supporting U.S. Department of War programs, cUAS systems, or mission-critical autonomous platforms
• Experience working with diverse or atypical data sources (e.g., Audio/Acoustics, RF signals, EO/IR imagery)
• Experience deploying and optimizing ML inference on edge or resource-limited compute systems
• Experience with Explainable/Auditable AI/ML tools and interpretable model design
• Experience with AI Software Development Tools (e.g., GitHub CoPilot, Claude)
Company:
Bringing online retail metrics, insights, and visibility you care about into your brick and mortar locations. Founded in 2019, the company is headquartered in Minnetonka, USA, with a team of 11-50 employees. The company is currently Early Stage.

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