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Machine Learning Engineer Intern Jobs in Detroit, MI

Machine Learning Engineer 3

Dearborn, MI ยท On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine ...

Senior Machine Learning Engineer

Warren, MI ยท On-site +1

$222K - $227K/yr

Machine Learning Frameworks, including TensorFlow and PyTorch; Mathematical Reasoning and Probability; Programming in C++ or Python; Experience with Robot Operating System (ROS), OpenCV, or PCL;

Senior Machine Learning Engineer

Warren, MI ยท On-site

$222K - $227K/yr

Machine Learning Frameworks, including TensorFlow and PyTorch; Mathematical Reasoning and Probability; Programming in C++ or Python; Experience with Robot Operating System (ROS), OpenCV, or PCL;

Senior Machine Learning Engineer

Detroit, MI ยท Remote

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat ...

Senior Machine Learning Engineer

Detroit, MI ยท On-site +1

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat ...

DIA Machine Learning Engineer

Dearborn, MI ยท On-site +1

$66K - $186K/yr

DIA Machine Learning Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the aforementioned ...

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Machine Learning Engineer Intern information

See Detroit, MI salary details

$23.3K

$39K

$80.5K

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

As of Jun 19, 2026, the average yearly pay for machine learning engineer intern in Detroit, MI is $38,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,700.00 and $42,100.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in Detroit, MI? The most popular types of Machine Learning Engineer jobs in Detroit, MI are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Detroit, MI? For Machine Learning Engineer Intern jobs in Detroit, MI, the most frequently searched job titles are:
What cities near Detroit, MI are hiring for Machine Learning Engineer Intern jobs? Cities near Detroit, MI with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in Detroit, MI as of June 2026, with employment types broken down into 2% As Needed, 82% Full Time, 15% Part Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $38,964 per year, or $18.7 per hour.
Machine Learning Engineer 3

Machine Learning Engineer 3

Saanvi Technologies

Dearborn, MI โ€ข On-site

$105K - $126K/yr

Contractor

Posted 6 days ago


Job description

Machine Learning Engineering Engineer 3

Dearborn, MI

W2

Position Description:

We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine Learning, Large Language Models (LLMs), and emerging Agentic AI capabilities to transform business processes and drive operational efficiency. This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable, production-ready AI systems that generate measurable business value. The ideal candidate will have hands-on experience building and operationalizing AI/ML solutions in enterprise environments, with a strong focus on Generative AI, intelligent automation, and cloud-native architectures. Key Responsibilities Design, develop, and deploy machine learning models, including predictive, optimization, and Generative AI solutions. Build end-to-end AI workflows encompassing data ingestion, feature engineering, model training, deployment, monitoring, and continuous improvement. Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services that seamlessly integrate with enterprise applications and business processes. Establish and maintain MLOps practices, including automated training, deployment, monitoring, retraining, and performance management. Ensure AI solutions are reliable, scalable, secure, and optimized for production environments. Collaborate closely with business and technical stakeholders to identify opportunities and translate business challenges into AI-driven solutions. Monitor model performance and implement ongoing enhancements based on business feedback, operational metrics, and evolving requirements. Stay current with advancements in AI, Generative AI, Agentic AI, and MLOps to continuously improve solution capabilities and delivery approaches. Required Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related discipline. Strong programming experience in Python, including backend development, API design, automation, and software engineering best practices. Hands-on experience building, deploying, and supporting machine learning models in production environments. Experience with machine learning frameworks such as Scikit-learn, TensorFlow, and/or PyTorch. Practical experience developing applications using Large Language Models (LLMs), prompt engineering, and Generative AI technologies. Experience building AI solutions on cloud platforms such as GCP and/or AWS. Strong understanding of software development lifecycle, version control, testing, and deployment practices. Excellent analytical, problem-solving, and communication skills. Ability to thrive in a fast-paced, agile environment with evolving priorities and business needs

Skills Required:

Python, Machine Learning, Data Science, GCP, Big Query

Experience Required:

Engineer 3 Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang. 6+ years in IT; 4+ years in development Experience designing and implementing Agentic AI solutions, multi-step workflows, autonomous agents, and tool-calling architectures. Experience with AI orchestration frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar technologies. Hands-on experience with MLOps tools and platforms including MLflow, Airflow, Vertex AI, SageMaker, Kubeflow, or equivalent solutions. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Familiarity with vector databases, embeddings, Retrieval-Augmented Generation (RAG), and semantic search architectures. Experience working with enterprise-scale data environments, data lakes, and large datasets. Experience optimizing AI systems for scalability, performance, reliability, and cost efficiency. Experience building AI-powered products, dashboards, analytics solutions, or intelligent automation platforms.

Experience Preferred:

Self-starter with the ability to work independently and navigate ambiguity. Strong communicator capable of engaging both technical and non-technical stakeholders. Collaborative team player who can effectively partner across business and technology functions. Innovative thinker with a passion for applying AI to solve real-world business challenges. Results-oriented mindset focused on delivering practical, scalable, and impactful solutions.

Education Required:

Bachelor's Degree

Education Preferred:

Additional Safety Training/Licensing/Personal Protection Requirements:

Additional Information :

4 days in the office Python (advanced), SQL Machine Learning & Deep Learning LLMs, Prompt Engineering, RAG, Embeddings Agentic AI / AI Agents / Tool Calling Vector Databases ML Frameworks: Scikit-learn, TensorFlow, PyTorch MLOps: MLflow, Airflow, CI/CD, model deployment & monitoring Cloud: AWS or GCP Docker, Kubernetes API development (FastAPI / Flask) Data pipelines (ETL), data lakes/warehouses Strong system design & production AI experience


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About Saanvi Technologies

Sourced by ZipRecruiter

Saanvi Technologies is a staffing company that specializes in providing IT professionals to businesses. Our employees are experts in their field, and have the skills and experience necessary to help businesses grow and succeed. Saanvi Technologies is dedicated to helping businesses achieve their goals, and they have a proven track record of success. Our employees are qualified and reliable, and they always go above and beyond to meet the needs of their customers.

Company size

51 - 200 Employees

Headquarters location

Farmington, MI, US

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