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Artificial Intelligence Machine Learning Engineer Jobs in Michigan

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... GCP, Big Data, Artificial Intelligence & Expert Systems, API * GCP - Experience deploying and ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our ...

Stefanini

Machine Learning Engineer

Allen Park, MI · On-site

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach out to Navneet Pathak at / We are looking for a candidate who is responsible for predicting and/ or ...

FastTek

Machine Learning Engineer

Dearborn, MI

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions leveraging Machine Learning, Large Language ...

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Artificial Intelligence Machine Learning Engineer information

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$27.5K

$112.2K

$168.7K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for artificial intelligence machine learning engineer in Michigan is $112,234.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $135,100.00 per year, depending on experience, location, and employer.

What is an Artificial Intelligence Machine Learning Engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by Artificial Intelligence Machine Learning Engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior AI or machine learning engineers, research directors, or executive positions in artificial intelligence. These roles often require advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch, along with leadership responsibilities and a strong track record of innovation. Compensation at this level reflects extensive expertise, strategic impact, and often involves stock options or bonuses in addition to base salary.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What engineers make $500,000?

Artificial Intelligence and Machine Learning Engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning, and work in high-demand industries like tech or finance. Compensation often includes base salary, bonuses, and stock options, particularly at senior levels or in leadership roles.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

Is AI ML engineer in demand?

AI and ML engineers are in high demand across various industries due to the increasing adoption of artificial intelligence technologies. Companies seek professionals skilled in programming languages like Python, machine learning frameworks, and data analysis to develop and implement AI solutions, leading to strong job growth and competitive salaries in this field.

How much do AI ML engineers make?

AI ML engineers typically earn a median salary ranging from $100,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in deep learning, natural language processing, or cloud platforms can command higher salaries, often exceeding $200,000.
What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Michigan? For Artificial Intelligence Machine Learning Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Michigan look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Michigan are:
What cities in Michigan are hiring for Artificial Intelligence Machine Learning Engineer jobs? Cities in Michigan with the most Artificial Intelligence Machine Learning Engineer job openings:
Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Michigan as of June 2026, with employment types broken down into 87% Full Time, 8% Part Time, 3% Contract, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $112,234 per year, or $54 per hour.
Machine Learning Engineer

Machine Learning Engineer

FastTek

Dearborn, MI

$105K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 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.