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Internship Edge Ai Machine Learning Jobs in Minnesota

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 ... on edge or resource-limited compute systems • Experience with Explainable/Auditable AI/ML tools ...

Kitware

Machine Learning Engineer

Minneapolis, MN

$85K - $125K/yr

We seek to advance AI, CV, and other related fields through research and development and ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

We seek to advance AI, CV, and other related fields through research and development and ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

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Internship Edge Ai Machine Learning information

What is an internship edge AI machine learning?

Internship Edge AI Machine Learning positions are entry-level roles designed for students or recent graduates who want hands-on experience working with artificial intelligence and machine learning technologies, especially those related to 'edge' computing. These internships focus on developing, optimizing, and deploying AI/ML models that run on edge devices such as smartphones, IoT devices, and embedded systems, rather than in the cloud. Interns typically assist in research, data preparation, model training, and software development while gaining industry-relevant skills. These roles are ideal for individuals interested in both hardware and software aspects of AI. The experience gained can be valuable for future careers in data science, machine learning engineering, or AI research.

What types of projects can I expect to work on during an internship in edge AI and machine learning?

As an intern in Edge AI and Machine Learning, you will likely work on projects that involve developing and optimizing machine learning models for deployment on edge devices such as smartphones, IoT sensors, or embedded systems. Typical tasks include data preprocessing, model training and evaluation, and implementing algorithms with resource constraints in mind. You may also collaborate with hardware engineers and software developers to ensure that your solutions run efficiently on limited hardware. This hands-on experience provides a strong foundation for understanding real-world AI deployment challenges and can open doors to more advanced roles in the future.

What are the key skills and qualifications needed to thrive as an internship edge AI machine learning professional, and why are they important?

To thrive in an Internship Edge AI Machine Learning role, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by coursework or relevant projects. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud or edge computing platforms is highly valuable. Strong analytical thinking, problem-solving abilities, and effective teamwork skills help you adapt and contribute meaningfully in collaborative research and development environments. These competencies are crucial for innovating and deploying machine learning models on edge devices, ensuring impactful real-world AI solutions.

What is the difference between Internship Edge Ai Machine Learning vs Data Analyst?

AspectInternship Edge Ai Machine LearningData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in statistics, mathematics, or related field; proficiency in data tools
Work EnvironmentInternship setting, collaborative teams, research-focusedOffice environment, data-driven decision-making teams
Employer & Industry UsageTech companies, startups, research institutionsBusiness, finance, healthcare, marketing sectors

Internship Edge Ai Machine Learning roles typically focus on foundational skills in AI and machine learning, often as entry-level or internship positions. Data Analysts work across various industries analyzing data to inform business decisions. While both roles involve working with data, AI internships emphasize machine learning models, whereas Data Analysts focus on data interpretation and reporting.

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Internship Edge Ai Machine Learning jobs near you

Data Scientist, Principal - AI Product Engineering (Minneapolis)

Blue Shield of CA

Minneapolis, MN • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

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.

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