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Internship Deep Reinforcement Learning Jobs in Michigan

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

... deep learning methods, alongside prompt engineering, retrieval-augmented generation (RAG), and ... fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning

May Mobility

Director, Autonomy Behavior

Ann Arbor, MI · On-site

Deep technical knowledge and demonstrated success in delivering innovative solutions in one or more of the fields of planning, autonomous decision making, reinforcement learning, and computational ...

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

... deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized ...

ALTEN Technology USA

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

Machine Learning & Deep Learning (supervised, unsupervised, reinforcement learning) * Support delivery teams with hands-on guidance and expert oversight * Drive development of AI & Data offerings ...

Magna

Robotics AI Algorithm- R&D Summer 2026

Troy, MI · On-site

... Deep Learning, Reinforcement learning, Transformers, Natural Language Processing (NLP), Diffusion models, Gen-AI). • Create representative case study to understand solution capabilities and ...

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Internship Deep Reinforcement Learning information

What types of projects or tasks can I expect to work on during a deep reinforcement learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in deep reinforcement learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

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Internship Deep Reinforcement Learning jobs near you

Machine Learning Engineer

FastTek

Dearborn, MI

$105K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 26 days ago

Job description

Machine Learning Engineer #1054987
Job Description:
  • Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions — including Generative AI and Large Language Model (LLM) systems — in areas such as computer vision, perception, localization, natural language processing, and conversational AI.
  • They automate and optimize the end-to-end ML and Gen AI model lifecycle using expertise in experimental methodologies, statistics, prompt engineering, and coding for tool building and analysis.
  • Design and develop innovative ML models, Gen AI systems, and software algorithms — including LLM-based architectures (e.g., transformer models, RAG pipelines, fine-tuned foundation models) — to solve complex business problems in both structured and unstructured environments

Skills Required:
GCP, Big Data, Artificial Intelligence & Expert Systems, API
  • GCP - Experience deploying and managing services on Google Cloud Platform, including Compute Engine, Cloud Storage, IAM, and Cloud Functions. For example, designing and implementing a cloud-native application architecture using GKE (Google Kubernetes Engine) with Cloud SQL and Pub/Sub.
  • Big Data - Experience working with large-scale data processing frameworks such as Apache Spark, Dataflow, or BigQuery. For example, building ETL pipelines that process terabytes of daily event data and transform it for downstream analytics.
  • Data Warehousing - Experience designing and maintaining data warehouse solutions (e.g., BigQuery, Snowflake, Redshift). For example, modeling a star schema for a retail analytics platform that supports reporting on sales, inventory, and customer behavior.
  • Artificial Intelligence & Expert Systems - Experience developing or integrating AI/ML models and rule-based expert systems. For example, building a classification model using Vertex AI to predict customer churn, or implementing a rule engine that automates underwriting decisions.
  • API - Experience designing, building, and consuming RESTful or gRPC APIs. For example, developing a versioned REST API with OAuth 2.0 authentication that serves as the integration layer between a mobile application and backend microservices.

Skills Preferred:
Google Cloud Platform
  • Google Cloud Platform - Familiarity with advanced GCP services beyond core compute and storage, such as Vertex AI, Dataflow, Cloud Composer (Airflow), and BigQuery ML. For example, using Cloud Composer to orchestrate scheduled data pipelines that feed into a BigQuery data warehouse.

Experience Required:
  • Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides.
  • 10+ years in IT
  • 8+ years in development

Experience Preferred:
  • Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
  • Proven experience in building and deploying RAG systems, including the use of **Vector Databases**.
  • Proficiency in Python programming.
  • Solid experience with SQL for data manipulation and querying.
  • Hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML.
  • Basic understanding and practical experience with Machine Learning model fine-tuning.
  • Familiarity with data engineering concepts and practices.
  • Expertise in prompt engineering techniques for interacting with LLMs.
  • Experience with the OpenAI SDK.
  • Experience developing robust APIs, preferably with **FastAPI**.
  • Proficiency with **version control systems (e.g., Git)**.
  • Experience with **containerization technologies (e.g., Docker)**.

Education Required:
  • Bachelor's Degree

Education Preferred:
  • Certification Program

Additional Information:
  • Design, build, maintain, and optimize scalable ML and Gen AI pipelines, architecture, and infrastructure, including vector databases, embedding stores, and LLM serving layers
  • Use machine learning and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and deep learning methods, alongside prompt engineering, retrieval-augmented generation (RAG), and parameter-efficient fine-tuning (PEFT/LoRA) to develop and evaluate algorithms that improve product/system performance, quality, data management, and accuracy
  • Adapt machine learning and Gen AI capabilities to domains such as virtual reality, augmented reality, object detection, tracking, classification, terrain mapping, intelligent document processing, and AI-powered agent workflows
  • Train, fine-tune, and re-train ML models and LLMs as required, including supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning
  • Deploy ML models, LLMs, and AI agents into production; run simulations and evaluations (including LLM evals and red-teaming) for algorithm development and test various scenarios
  • Automate model deployment, training, re-training, and Gen AI pipeline orchestration, leveraging principles of agile methodology, CI/CD/CT, MLOps, and LLMOps — including guardrail integration, prompt versioning, and observability tooling
  • Enable model management for model versioning, traceability, and governance — including responsible AI practices, bias evaluation, hallucination mitigation, and content safety controls — to ensure modularity and consistency across environments for both ML and Gen AI systems

Additional Info:
At FastTek Global, Our Purpose is Our People and Our Planet. We come to work each day and are reminded we are helping people find their success stories. Also, Doing the right thing is our mantra. We act responsibly, give back to the communities we serve and have a little fun along the way.
We have been doing this with pride, dedication and plain, old-fashioned hard work for 24 years!
FastTek Global is financially strong, privately held company that is 100% consultant and client focused.
We've differentiated ourselves by being fast, flexible, creative and honest. Throw out everything you've heard, seen, or felt about every other IT Consulting company. We do unique things and we do them for Fortune 10, Fortune 500, and technology start-up companies.
Our benefits are second to none and thanks to our flexible benefit options you can choose the benefits you need or want, options include:
  • Medical and Dental (FastTek pays majority of the medical program)
  • Vision
  • Personal Time Off (PTO) Program
  • Long Term Disability (100% paid)
  • Life Insurance (100% paid)
  • 401(k) with immediate vesting and 3% (of salary) dollar-for-dollar match

Plus, we have a lucrative employee referral program and an employee recognition culture.
FastTek Global was named one of the Top Work Places in Michigan by the Detroit Free Press in 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023!
To view all of our open positions go to: https://www.fasttek.com/fastswitch/findwork
Follow us on Twitter: https://twitter.com/fasttekglobal
Follow us on Instagram: https://www.instagram.com/fasttekglobal
Find us on LinkedIn: https://www.linkedin.com/company/fasttek
You can become a fan of FastTek on Facebook: https://www.facebook.com/fasttekglobal/
AI & Hiring Disclosure
We use AI tools to support parts of our hiring process, such as reviewing applications and identifying potential matches. These tools are designed to promote efficiency, consistency, and fairness, and they are always used under human oversight.
All personal data collected is used solely for recruitment purposes, and you have the right to know, access, or request deletion of your data at any time, subject to legal limits.
If AI will be used in a video interview, you'll be informed in advance and asked for your consent, with the option to opt out.
Our tools are regularly reviewed to detect potential bias and to ensure compliance with all applicable laws and our commitment to inclusive hiring.
To learn more or exercise your rights, please contact us at info@fasttek.com.