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Patterned Learning Ai Jobs in Michigan (NOW HIRING)

AI / Machine Learning Development * Design, develop, and train machine learning and deep learning ... Architect orchestration patterns for planning, task decomposition, memory, context management, and ...

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

Artificial Intelligence & Expert Systems, Machine Learning, Data Science, Data Modeling, Software ... Strong technical expertise in cloud services (GCP/Vertex AI) and data integration patterns * Strong ...

AI and Data Science Engineer III

Detroit, MI · On-site +1

$113K - $136K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning ... AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms ...

... patterns/ recommendations from raw data, leveraging data science methodologies including Machine ... Agentic AI Orchestrator : A deployed multi-agent system that autonomously monitors the middleware ...

... patterns/ recommendations from raw data, leveraging data science methodologies including Machine ... Agentic AI Orchestrator: A deployed multi-agent system that autonomously monitors the middleware ...

... patterns/ recommendations from raw data, leveraging data science methodologies including Machine ... Agentic AI Orchestrator : A deployed multi-agent system that autonomously monitors the middleware ...

Google AI Lead Architect

Detroit, MI · On-site

$54.50 - $74.75/hr

Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient and ... Preferred : • Google Professional Machine Learning Engineer certification or the equivalent ML ...

... patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and ... Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning ...

Senior Engineer, AI

Novi, MI · On-site

$98K - $134K/yr

Artificial Intelligence & Machine Learning Worker Type Reference: Regular - Permanent Pay Rate Type ... patterns over structured and unstructured enterprise data. * Contribute to enterprise data and AI ...

... trends and patterns * Build predictive models and machine-learning algorithms * Writing and ... Facilitate the internal and external data science & AI network * Be a specialist on specific data ...

... machine learning (ML), generative artificial intelligence (GenAI), and agentic systems in ... Creates reference architectures, defines security requirements and patterns for model training ...

... machine learning (ML), generative artificial intelligence (GenAI), and agentic systems in ... Creates reference architectures, defines security requirements and patterns for model training ...

... conceptual patterns into validated, repeatable implementation blueprints. You are a hybrid ... Learning and development opportunities * Discount programs with various manufacturers and retailers

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Patterned Learning Ai information

What are some typical challenges faced by Patterned Learning AI professionals in implementing AI-driven solutions within organizations?

Patterned Learning AI professionals often encounter challenges such as integrating AI models with existing legacy systems, ensuring high-quality and representative training data, and aligning AI solutions with specific business objectives. Collaboration across multidisciplinary teams—including data scientists, software engineers, and business stakeholders—is essential for successful deployment. Additionally, professionals must stay updated on evolving AI technologies and best practices to maintain model accuracy and address ethical considerations.

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

To thrive as a Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (especially Python), and a degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as familiarity with cloud computing platforms and data management tools, is essential. Excellent problem-solving skills, creativity, and clear communication are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies are vital for developing reliable AI systems that solve real-world problems and drive innovation.

What is the difference between Patterned Learning Ai vs Data Scientist?

AspectPatterned Learning AiData Scientist
Required CredentialsTypically requires machine learning, AI, or computer science degrees; certifications in AI toolsRequires degrees in statistics, computer science, or related fields; often certifications in data analysis
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed by AI-focused organizations developing intelligent systemsEmployed across industries for data analysis, predictive modeling, and decision support

Patterned Learning Ai primarily focuses on developing AI models and algorithms, often requiring specialized technical skills. Data Scientists analyze data to extract insights and inform business decisions. While both roles involve data and machine learning, Patterned Learning Ai is more centered on creating AI systems, whereas Data Scientists interpret data for strategic purposes.

What is Patterned Learning AI?

Patterned Learning AI refers to artificial intelligence systems designed to recognize, learn from, and replicate patterns in data. These systems use algorithms to identify trends, correlations, and structures within large datasets, enabling them to make predictions or automate decision-making processes. Patterned Learning AI is commonly used in fields like image recognition, natural language processing, and predictive analytics. Its applications help businesses and researchers uncover hidden insights, streamline operations, and improve accuracy in various tasks.
What cities in Michigan are hiring for Patterned Learning Ai jobs? Cities in Michigan with the most Patterned Learning Ai job openings:
Infographic showing various Patterned Learning Ai job openings in Michigan as of June 2026, with employment types broken down into 62% Full Time, 32% Part Time, and 6% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
Technical Lead (Applied AI)

Technical Lead (Applied AI)

X by 2

Detroit, MI

Full-time

Posted 15 days ago


Job description

X by 2 is a technology consulting firm specializing in healthcare and insurance transformation. For over 25 years, we have partnered with leading organizations across North America — from strategy and architecture to system modernization, data analytics, and AI — delivering high-impact solutions from start to finish. We're agile, collaborative, and deeply committed to doing consulting the way it was meant to be done.

We are looking for a Technical Lead who will lead the design and development of AI solutions within enterprise environments for our clients. You'll combine hands-on engineering with leadership, guiding architecture decisions, mentoring teams, and building solutions.

Responsibilities
  • Technical Leadership & Architecture

    • Lead architecture, design, development, testing, and deployment of enterprise software solutions (applications, data, integration, AI agents, AI models)

    • Participate in strategy and roadmap discussions, architecture definition, and technology evaluations

    • Mentor engineers through design reviews, code reviews, and technical guidance

    • Quickly evaluate and adopt new tools, technologies, and platforms to build prototypes and proofs-of-concept

    • Drive adoption of AI solutions and collaborate with engineering teams, product leaders, and domain experts to deliver results

  • Software Engineering

    • Design, develop, and maintain scalable, production-grade enterprise applications using modern languages and frameworks (Python, Java, C#, JavaScript)

    • Define and enforce coding standards, best practices, and design patterns across the team

    • Build and maintain CI/CD pipelines, infrastructure-as-code, and cloud-deployed services (AWS, Azure)

    • Integrate enterprise systems via APIs, event-driven architectures, and messaging platforms

    • Identify and resolve performance bottlenecks, technical debt, and system reliability issues

  • Data & Analytics

    • Work with large, complex datasets and ensure data quality and integrity

    • Analyze data to generate insights that inform both model development and broader solution strategy

    • Collaborate with stakeholders to translate business problems into data-driven solutions

  • AI / Machine Learning Development

    • Design, develop, and train machine learning and deep learning models for healthcare and insurance use cases

    • Perform data modeling and feature engineering to support model development

    • Develop custom model metrics and approaches tailored to specific business problems

    • Ensure models are scalable, reliable, and integrated into production systems

  • Agentic AI Development

    • Design and develop LLM-powered workflows and agentic systems that help users complete complex tasks, retrieve information, reason over enterprise data, or interact with internal systems.

    • Integrate LLMs with tools, APIs, databases, documents, and enterprise platforms using patterns such as function calling, MCP, RAG, and structured tool use.

    • Architect orchestration patterns for planning, task decomposition, memory, context management, and human-in-the-loop review where appropriate.

    • Develop orchestration layers to manage agent planning, memory, task decomposition, and execution loops

    • Evaluate agentic systems for correctness, reliability, safety, observability, auditability, and harden them for production readiness.

    • Stay current with emerging AI frameworks and platforms, selecting tools pragmatically based on client needs.

Qualifications
  • Experience

    • 6+ years of experience in software engineering designing and developing enterprise applications, data/analytics solutions, and/or integration solutions

    • 1+ years of providing technical leadership as Tech Lead, Lead Engineer, or Architect

    • 1+ years in developing AI agents and/or AI model development and training

  • Education

    • Bachelor's Degree in Computer Science, Software Development, Software Engineering, or Computer Engineering

    • (Optional) Master's Degree or Minor in AI/Machine Learning or Statistics

  • AI Engineering Skills (Two or More)

    • Agentic AI: building and integrating autonomous AI agents using LLM APIs and orchestration frameworks (e.g., Anthropic Claude, OpenAI GPT, LangChain, CrewAI, AutoGen, MCP)

    • Machine Learning & Deep Learning: developing and training models using standard ML/DL frameworks (e.g., TensorFlow, PyTorch, scikit-learn)

    • Data Engineering & Feature Engineering: building data pipelines, performing feature engineering, and ensuring data quality across large, complex datasets

    • Context Engineering: Agentic SQL retrieval, MCP integration, agentic tool use, as well as vector databases & RAG techniques implementing retrieval-augmented generation patterns using vector stores (e.g., Pinecone, Weaviate, pgvector, ChromaDB), .

    • LLM Prompt Engineering & Fine-Tuning: designing and evaluating effective prompts, system instructions, and fine-tuning strategies for production LLM applications

    • AI Evaluation & Production Readiness: defining evaluation methods, testing model behavior, monitoring performance, and addressing reliability, safety, explainability, and auditability concerns

  • What We're Looking For

    • You move fluidly between writing code and leading a room — equally comfortable in a design review as you are in a pull request

    • You have strong opinions about architecture and aren't afraid to share them, but you know when to listen and adapt

    • You take ownership seriously — on small teams, your decisions have real impact and you're energized by that, not intimidated

    • You're genuinely curious about AI, not just checking a box — you've experimented with agentic systems, LLMs, or ML tools on your own terms

    • You communicate clearly with both engineers and non-technical stakeholders, and can translate complexity without dumbing it down

Location
  • Metro Detroit or North Carolina Research Triangle (Raleigh, Durham, Chapel Hill)

  • Hybrid: flexibility to work remotely, but not fully remote

  • Travel to X by 2 offices (Farmington Hills, MI) and client sites (within US) is required when requested

Work Environment and Culture
  • Work alongside smart, collaborative people who continually challenge and invest in each other

  • Partner with seasoned architects to solve hard problems and challenge assumptions

  • Small teams mean real ownership, with growth and responsibilities driven purely by individual performance

  • Everyone has a voice and is encouraged to shape the company by sharing their interests, ideas, and feedback

Compensation & Benefits
  • Base salary $143K–$185K, depending on experience, plus profit sharing

  • Annual raises and promotions based on performance

  • 401(k) with employer match

  • Comprehensive health, vision, dental, life, and disability insurance coverage, plus voluntary benefits and HSA with employer contribution

  • Home Office Reimbursement, Health and Wellness Reimbursement, and Professional Dress Allowance

  • Professional Self-Development Program

  • Paid vacation, unlimited sick days (as needed), and holidays

  • Company-sponsored social events and an employee recognition rewards program

Sound Like You?
We're not looking for someone who has done everything — we're looking for someone who is driven to. If you thrive in environments where you can move fast, go deep, and make a real difference for clients solving complex problems in healthcare and insurance, we'd love to hear from you.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.


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About X by 2

Sourced by ZipRecruiter

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Farmington Hills, MI, US

Year founded

1998