ZipRecruiter

Log In

1

Embedded Machine Learning Internship Jobs in Arvada, CO

Judge Group, Inc.

Data Science Engineer

Westminster, CO · On-site

$100K - $140K/yr

In this role, you will develop the machine-learning components and integration infrastructure that ... You will work closely with astrodynamics and embedded-systems teams to ensure that models reflect ...

PNC Bank

Technology Undergraduate Intern

Arvada, CO

$18 - $35/hr

Past example internship projects include machine learning development, automating current manual processes, infrastructure provisioning, and outer API servicing. PNC looks for interns to bring a ...

TIFIN

AI Engineering Intern, TIFIN.ai

Boulder, CO

$17 - $25/hr

Familiarity through former internships, coursework or research with machine learning or AI, APIs, backend development COMPENSATION $17-25/hour Note that interns do not qualify for benefits or equity ...

Overwatch Agriculture

Software Engineer

Boulder, CO · On-site

$125K - $180K/yr

... constrained embedded systems. * Ability to thrive in a fast-moving, collaborative, small team ... machine learning, or a related field. * BS or MS in Computer Science, Computer Engineering ...

previous pagenext page

Showing results 21-40

All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Arvada, CO

Embedded Machine Learning Internship information

See Arvada, CO salary details

$26K

$43.3K

$89.6K

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

As of Aug 20, 2026, the average yearly pay for embedded machine learning internship in Arvada, CO is $43,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,100.00 and $46,800.00 per year, depending on experience, location, and employer.

What is an embedded machine learning internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an embedded machine learning internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an embedded machine learning intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.

What are popular job titles related to Embedded Machine Learning Internship jobs in Arvada, CO?

For Embedded Machine Learning Internship jobs in Arvada, CO, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Internship jobs in Arvada, CO look for?

The top searched job categories for Embedded Machine Learning Internship jobs in Arvada, CO are:

Embedded Machine Learning Internship jobs near you

Data Scientist, Principal - AI Product Engineering (Denver)

Blue Shield of CA

Denver, CO • On-site

Full-time

Posted 2 days ago

New

Job description

Your Role

The AI & Machine Learning team works in partnership across the enterprise to accelerate business outcomes by applying AI, machine learning, and generative AI to build intelligent products that create intelligence at scale. Reporting to the Director, AI & Machine Learning, the Data Scientist, Principal will lead the development and deployment of novel applications that leverage generative AI models. This role focuses on rapidly developing new features and working across partner teams to deliver solutions and maximize impact, translating cutting-edge AI research into real-world products and taking features from 0 to 1. You will design, build, and ship production-grade AI products including LLM-powered applications, AI agents and copilots, retrieval-augmented generation (RAG) and search, and AI-enabled automation embedded directly into customer-facing applications and enterprise workflows such as claims, payment integrity, clinical insights, and member experience. You will set the technical direction for how AI is applied across the organization.

Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.

Your Knowledge and Experience
  • Bachelor's degree in computer science, a quantitative discipline, or equivalent practical experience; Master's degree or PhD preferred
  • 10 years of prior relevant experience in data science, machine learning, applied AI/ML, software engineering, or advanced analytics
  • Proven track record of building and shipping software products rapidly, not just developing models or analyses
  • Strong software engineering skills and proficiency in Python, including building APIs and backend services
  • Experience leading ML design and optimizing ML infrastructure, model deployment, evaluation, and data processing, and working with machine learning frameworks and libraries
  • Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph
  • Hands-on experience building applications that leverage generative AI models, including prompt engineering and retrieval-augmented generation (RAG)
  • Experience with generative AI research or applications preferred
  • Experience designing agent-based systems and orchestration frameworks preferred
  • Experience with cloud computing platforms and infrastructure (e.g., Azure, Google Cloud, or AWS), and scalable data processing with SQL or Spark preferred
  • Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management preferred
  • Experience rapidly developing and shipping software in a fast-paced, customer-facing environment, adapting to changing priorities preferred
  • Understanding of responsible AI and governance for regulated or healthcare environments preferred
Hybrid

This role requires employees to be in-office based on our hybrid workplace model, balancing purposeful in-person collaboration with flexibility. For most teams, this means coming into the office two days each week.

Employees living more than 50 miles from an office location will work with their manager to determine in-office time based on business need.

#LI-CM1

#J-18808-Ljbffr

Apply