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Mlflow Jobs in Michigan (NOW HIRING)

Kobie Marketing

AI Engineer

Detroit, MI · Remote

Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry * Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression) * Fluency with Git, Docker, and ...

Kobie Marketing

AI Engineer

Detroit, MI · On-site +1

Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry * Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression) * Fluency with Git, Docker, and ...

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

Demonstrated experience with MLOps principles and tools (e.g., Azure ML, AWS SageMaker, GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs. * Strong technical expertise ...

Corning

What would be a plus? - Exposure to Databricks, MLflow, Kubeflow, Docker, Kubernetes, CI/CD, or other MLOps/DevOps tools. - Experience with manufacturing, industrial, process, plant, or production ...

Stellantis

AI Validation Engineer

Auburn Hills, MI · On-site

Familiarity with ML experiment tracking and pipeline orchestration tools (MLflow, Weights & Biases, Kubeflow, or equivalent). * Experience with CI/CD systems (Jenkins, GitLab CI, GitHub Actions) for ...

Corning

$95K - $130K/yr

What would be a plus? - Experience with Databricks, MLflow, Kubeflow, Docker, Kubernetes, cloud or on-premise deployment, and enterprise systems integration.- Experience deploying ML solutions in ...

Little Caesars

Applied AI Engineer

Detroit, MI · On-site

$113K - $136K/yr

... serving, MLflow, and related cloud services such as Azure AI Foundry, Microsoft Fabric, or Azure Data Factory Working Conditions: This position may require minimal travel to vendor locations ...

Ilitch

Applied AI Engineer

Detroit, MI

Experience with Databricks, notebooks, model serving,MLflow, and related cloud services such as Azure AI Foundry, Microsoft Fabric, or Azure Data Factory Working Conditions: * This position may ...

OneMagnify

Data Scientist

Detroit, MI · On-site

$120 - $170/hr

Collaborate with engineering teams to implement MLOps practices--including model deployment, monitoring, and end‑to‑end lifecycle management using tools such as MLflow. * Adhere to data ...

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Mlflow information

What is the difference between Mlflow vs Data Scientist?

AspectMlflowData Scientist
Required CredentialsKnowledge of machine learning tools, Python, and data managementDegree in Data Science, Statistics, or related field; programming skills
Work EnvironmentData science teams, machine learning projects, software developmentResearch, data analysis, model development, cross-functional teams
Employer & Industry UsageTech companies, AI startups, data-driven organizationsVarious industries including tech, finance, healthcare, and retail

While Mlflow is a platform for managing the machine learning lifecycle, a Data Scientist focuses on analyzing data and building models. Mlflow tools support Data Scientists in tracking experiments, but the roles differ in scope and responsibilities.

What are popular job titles related to Mlflow jobs in Michigan? For Mlflow jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Mlflow jobs in Michigan look for? The top searched job categories for Mlflow jobs in Michigan are:
What cities in Michigan are hiring for Mlflow jobs? Cities in Michigan with the most Mlflow job openings:
Mlflow jobs near you

AI Engineer

Kobie Marketing

Detroit, MI • Remote

Full-time

Re-posted yesterday

Job description

Join a National Top Workplace 
 
Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We're always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world's most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. 
 
Join Us from Anywhere 
While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with: 

         Flexible Time Off to recharge when needed 
         Nine Company-Wide Holidays 
         A diverse suite of benefits prioritizing your growth, development, and personal well-being 

Discover more about our perks and benefits here. 
 
Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. 


About the team and what we'll build together

Kobie runs some of the largest loyalty programs in the world. We're building an internal agent platform on Amazon AgentCore that automates analyst workflows, surfaces insights from program data in Snowflake, and gives our teams and clients an LLM-native way to work with complex loyalty logic.

We're looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production. This is not a research role. You'll prototype, ship, monitor, and iterate on features used by real teams

Our team tends to be people who reason carefully, ship working code,and pick up new tools without a lot of handholding. There's no single path into this role. We value the impact of what you've built and your track record of building things that hold up.

How you will make an impact

Agent Development

  • Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory
  • Package agent harnesses for the AgentCore Runtime with appropriate context, tools, skills, and subagents that fit cleanly into production flows and scenarios
  • Write the tools and skills agents use  API integrations, SQL queries against Snowflake, Snowflake backed knowledge retrieval with clear contracts and Pydantic validation

Evaluation and Reliability

  • Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore Evaluations, and wire them into CI
  • Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt-injection protections, and hallucination mitigation
  • You own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks

Collaboration

  • Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex Search Services)
  • Contribute to refining our internal engineering patterns as the stack evolves

What you need to be successful

Required

  • 3+ years of professional Python, with production experience building and operating services
  • 1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG
  • Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel
  • Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry
  • Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression)
  • Fluency with Git, Docker, and modern API frameworks
  • Clear written communication and the judgment to know when something is ready to ship

A bachelor's degree is not required. Equivalent practical experience: including bootcamps, self-taught work, career changes, or non-CS technical degrees counts.

Strongly Preferred

  • Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory, policy, guardrails, observability, awscli, evaluations
  • Experience with Snowflake, Snowpark, or Snowflake Cortex
  • Fluency in writing and reading SQL, as well as understanding semantic models.
  • Familiarity with multi-agent patterns: supervisor/router, subagent/handoff, reflection, human-in-the-loop
  • A considered view on where agents should and shouldn't act and comfort pushing back when "let's add an agent" isn't the right answer
  • Experience in Loyalty, MarTech, AdTech, or a comparable data rich B2B domain
Who we are  As a trusted partner, Kobie delivers market-leading, end-to-end loyalty solutions designed to enable customer experiences for the world's most successful brands. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level. We believe that our team's passion and expertise are the driving forces behind our success and are proud to be named a Top Workplaces in the USA, where the best and brightest in loyalty drive our mission of growing enterprise value through loyalty. 
 
A place for all We celebrate and embrace diversity at Kobie! 
Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race,color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law. 
 
We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values. 
 
Ready to join us? If you're ready to make an impact and grow in a supportive, innovative environment, we'd love to hear from you. Apply today and join the best and brightest in loyalty! 
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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