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Postdoctoral In Reinforcement Learning Jobs in Michigan

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Employees in this job function are responsible for designing, building, deploying, and scaling ... fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning

Megan soft Inc

AI Engineer (W2 Position)

Dearborn, MI · On-site

$50 - $55/hr

... process automation, reinforcement learning, virtual assistants and specialized programming ... Specialist Exp: 5+ experience in relevant field Skills Required: Artificial Intelligence & Expert ...

Eccalon LLC

AI Expert Robotics - onsite

Detroit, MI

Background in autonomous systems, mobile robots, or robotic arms * Experience with computer vision, deep learning, or reinforcement learning * Familiarity with simulation environments (e.g., Gazebo ...

Tata Consultancy Services

AI Researcher

Detroit, MI · On-site

... autonomously in the physical world. You will collaborate with interdisciplinary teams of ... From visual perception and SLAM to multimodal sensor fusion and reinforcement learning, you'll be ...

Covenant HealthCare

RESP CARE EXTERN

Saginaw, MI · On-site

Engages in reinforcement of patient/family teaching as delegated by the RRT shift Leaders. Encouraged to be proactive in seeking learning experiences. Performs and records complete physical ...

ALTEN Technology USA

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

Machine Learning & Deep Learning (supervised, unsupervised, reinforcement learning) * Support ... Experience in: * Generative AI technologies (LLMs, RAG pipelines, prompt engineering, API-based AI ...

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Postdoctoral In Reinforcement Learning information

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Reinforcement Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a Postdoctoral Researcher in Reinforcement Learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
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Infographic showing various Postdoctoral In Reinforcement Learning job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

FastTek

Dearborn, MI

$105K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 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.