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Machine Learning Manager Jobs in Michigan (NOW HIRING)

... 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 ...

Machine Learning Engineer

Dearborn, MI · Remote

$51.25 - $68.50/hr

Adapt machine learning to areas such as virtual reality, augmented reality, object detection ... Enable model management for model versioning and traceability to ensure modularity and symmetry ...

Machine Learning Engineer

Dearborn, MI

$105.50K - $126.60K/yr

Stefanini is looking for a Machine Learning Engineer (Dearborn, MI) For quick apply, please reach ... Relational Database Management System like MySQL, PostgreSQL, and SQL Server. Real-Time data ...

Machine Learning Engineer

Dearborn, MI

$105.20K - $126.30K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... GCP - Experience deploying and managing services on Google Cloud Platform, including Compute Engine ...

Machine Learning Engineer

Dearborn, MI

$105.50K - $126.60K/yr

Experience with project management tools such as Jira. * Strong understanding of Google Cloud Platform (Google Cloud Platform). * Experience with TensorFlow and machine learning operations (MLOps)

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Showing results 1-20

Machine Learning Manager information

See Michigan salary details

$44.5K

$71.2K

$102.8K

How much do machine learning manager jobs pay per year?

As of May 28, 2026, the average yearly pay for machine learning manager in Michigan is $71,217.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $80,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Michigan? The most popular types of Machine Learning jobs in Michigan are:
What are popular job titles related to Machine Learning Manager jobs in Michigan? For Machine Learning Manager jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Machine Learning Manager jobs? Cities in Michigan with the most Machine Learning Manager job openings:
Infographic showing various Machine Learning Manager job openings in Michigan as of May 2026, with employment types broken down into 70% Full Time, 20% Part Time, 3% Temporary, and 7% Contract. Highlights an 51% Physical, 5% Hybrid, and 44% Remote job distribution, with an average salary of $71,217 per year, or $34.2 per hour.

Machine Learning Engineer

Stefanini

Dearborn, MI

Other

Posted 14 days ago


Job description


Stefanini Group is hiring!
Stefanini is looking for a Machine Learning Engineer, Dearborn, MI (Onsite)
For quick apply, please reach out Saurabh Kapoor at /
You will be 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
ResponsibilitiesDesign, build, maintain, and optimize scalable ML and Gen AI pipelines, architecture, and infrastructure, including vector databases, embedding stores, and LLM serving layersUse 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 workflowsTrain, fine-tune, and re-train ML models and LLMs as required, including supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuningDeploy ML models, LLMs, and AI agents into production; run simulations and evaluations (including LLM evals and red teaming) for algorithm development and test various scenariosAutomate 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
Experience RequiredGoogle Cloud Platform - 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 into 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 behaviorArtificial 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.
Experience PreferredStrong 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 (Google Cloud Platform) 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).Google Cloud Platform - Familiarity with advanced Google Cloud Platform 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.
**Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives***
Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We also speak with you about the process, including interviews and job offers.
About Stefanini Group
The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.
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