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Machine Learning Engineer Intern Jobs in Detroit, MI

Systems Engineer Intern

Detroit, MI

$16.50 - $21.50/hr

As a Systems Engineer Intern, you'll work alongside experienced engineers to support the ... Put People First reflects our commitment to safety and care of each other, learning and development ...

Systems Engineer Intern

Detroit, MI · On-site

$16.50 - $21.50/hr

As a Systems Engineer Intern, you'll work alongside experienced engineers to support the ... Put People First reflects our commitment to safety and care of each other, learning and development ...

Systems Engineer Intern

Detroit, MI · On-site

$16.50 - $21.50/hr

As a Systems Engineer Intern, you'll work alongside experienced engineers to support the ... Put People First reflects our commitment to safety and care of each other, learning and development ...

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

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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 Jul 13, 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 July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $38,964 per year, or $18.7 per hour.

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Re-posted 18 days ago


Job description

Company Description

Hi there! We're Razorfish. We've been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What's different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.

Overview

We're seeking a Machine Learning Engineer to help design, build, and maintain production-grade ML systems across cloud platforms. This role blends software engineering and ML expertise to translate prototypes into scalable solutions. You'll own the full ML lifecycle from development and deployment to monitoring and optimization using tools like Databricks, Vertex AI, and other cloud-native platforms. Strong technical skills, collaboration, and a passion for delivering AI at scale are essential.

For this role, we expect the candidate to demonstrate a track record of: 1. Collaborating with Data Science teams to deploy ML solutions into production. 2. Hands-on MLOps experience, including model deployment, monitoring, and lifecycle management. 3. Designing data warehouses and orchestrating data pipelines to support scalable ML operations.

Responsibilities

ML System Development & Deployment

  • Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML)
  • Develop and integrate microservices, REST APIs, and webhooks for ML model serving
  • Implement CI/CD pipelines for automated model training, testing, and deployment
  • Create robust data processing workflows for model training and inference

MLOps & Infrastructure

  • Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines)
  • Implement model monitoring, versioning, and performance tracking systems
  • Design automated retraining pipelines and manage model lifecycle
  • Ensure reliability, scalability, and security of models in production
  • Optimize inference performance and cost efficiency across cloud platforms

Software Engineering Excellence

  • Write clean, maintainable, and well-documented code following best practices
  • Implement comprehensive testing strategies including unit, integration, and model testing
  • Contribute to technical design reviews and architecture decisions
  • Maintain high code quality standards and participate in code reviews

Cross-Functional Collaboration

  • Partner with data scientists to productionize research models and prototypes
  • Collaborate with data engineers to design efficient data pipelines and feature stores
  • Work with product teams to integrate ML capabilities into customer-facing applications
  • Participate in agile development processes and cross-functional project planning
  • Provide technical guidance and mentorship to junior team members
Qualifications

Education & Experience

  • Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field
  • 3-4 years of professional experience in ML engineering, software engineering, or data science
  • 2+ years of hands-on experience deploying and maintaining ML models in production
  • Experience working in collaborative, cross-functional team environments

Technical Skills

  • Programming Languages: Strong proficiency in Python and SQL (2+ years)
  • ML Frameworks: Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras
  • Cloud Platforms: Solid hands-on experience with GCP, AWS, or Azure
  • ML Platforms: Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks
  • Analytics & Feature Engineering: Proficient with BigQuery, Redshift, Azure Synapse
  • Distributed Processing: Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka
  • Workflow Orchestration: Experience with Airflow, Cloud Composer, Jenkins
  • Networking & Security: Understanding of cloud networking, security, and cost optimization
  • MLOps & DevOps: Familiarity with CI/CD, ML lifecycle management
  • API Development: Experience with REST APIs and microservices
  • Version Control: Proficiency with Git and collaborative development workflows

Core Competencies

  • Strong understanding of ML algorithms, model evaluation, and validation
  • Experience with data preprocessing, feature engineering, and performance tuning
  • Solid software engineering fundamentals and coding best practices
  • Awareness of data privacy, security, and ethical AI principles
  • Excellent collaboration skills with technical and non-technical stakeholders
  • Self-driven learner with curiosity about emerging ML technologies

Preferred Qualifications

Advanced Technical Skills

  • MLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines
  • Containerization: Docker; basic Kubernetes knowledge
  • Specialized ML: Exposure to NLP, computer vision, or deep learning
  • Modern ML: Familiarity with LLMs, RAG patterns, transformer architectures

 

Professional Experience

  • Agile development and cross-functional collaboration
  • Code review and technical documentation practices
  • Interest in mentorship and knowledge sharing
  • Experience with model validation and software testing principles
 Additional Information

The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include:

  • Paid Family Care for parents and caregivers for 12 weeks or more
  • Monetary assistance and support for Adoption, Surrogacy and Fertility
  • Monetary assistance and support for pet adoption
  • Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance
  • Tuition Assistance
  • Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more
  • Matching Gifts programs
  • Flexible working arrangements
  • 'Work Your World' Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility)
  • Business Resource Groups that support multiple affinities and alliances

The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents.

Razorfish is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances.

If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.

All your information will be kept confidential according to EEO guidelines.

Compensation Range: $87,210 to $119,300. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 9/1/25.

 Compensation Range: USD $87,210.00 - USD $119,300.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 11/15/2025.Employment Type: OTHER