Ann Arbor, MI

Data Jobs in Ann Arbor, MI

3 jobs found

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Today

Mid-Level AI Engineer

Experis Ann Arbor, MI

Ann Arbor, MI

Today

$50 - $54/hr Full time Agentic Ai Ai Agent Ai Agent Platform

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Job Description

Experis is hiring a Mid-Level AI Engineer to support AI product and platform teams in building production-ready solutions. This onsite role in Ann Arbor, MI focuses on engineering practical AI and Generative AI capabilities, including LLM integrations and retrieval-augmented generation (RAG), with responsible AI considerations.

You’ll design and deliver AI-enabled applications and services that aim to drive real business outcomes. The work includes building reliable LLM-powered systems, adding automated testing and monitoring, and improving model performance across quality, cost, and latency.

What you’ll do

Design, develop, test, and deploy AI-enabled applications and services that support real business outcomes.
Build and integrate Generative AI solutions using large language models (LLMs), including prompt and tool orchestration.
Develop AI agents, workflows, prompts, tools, and orchestration frameworks that can run reliably in production.
Implement retrieval-augmented generation (RAG), semantic search, and knowledge retrieval to improve answer quality and relevance.
Evaluate and benchmark AI model performance, then optimize for quality, cost, and latency while adding automated testing, monitoring, and observability.

What you bring

Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field.
3–6 years of software development experience, including 2+ years building AI/ML or Generative AI applications.
Strong programming skills in one or more of: Python, Java, C#, TypeScript/JavaScript.
Experience developing REST APIs and distributed services, with cloud experience in Azure, AWS, or GCP.
Solid software engineering fundamentals, including design patterns, testing, CI/CD, security, and observability.

Tools and technologies

Python, Java, C#, TypeScript, JavaScript, REST APIs, Azure, AWS, GCP, LLMs, prompt orchestration, tool orchestration, retrieval-augmented generation (RAG), semantic search, CI/CD, observability.

Compensation and benefits

Pay: USD 50–54 per hour. Location: Ann Arbor, MI (onsite). Minimum experience: 3 years.

Benefits include:

Medical and Prescription Drug Plans
Dental Plan
Vision Plan
Health Savings Account
Health Flexible Spending Account
Dependent Care Flexible Spending Account
Supplemental Life Insurance
Short Term and Long Term Disability Insurance
Business Travel Insurance
401(k), Plus Match
Weekly Pay

Upon completion of the waiting period, consultants are eligible for the same benefits listed above.

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14d ago

Service Supply Chain AI Engineer

KLA Ann Arbor, MI

Ann Arbor, MI

14d ago

$90k - $133k/yr Full time Analytics Artificial Intelligence Data Analysis

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Job Description

KLA Services is hiring a Service Supply Chain AI Engineer to build and productionize AI/ML and graph-based tools that support spares planning decisions.

Responsibilities

Develop and maintain internal tools, including apps, dashboards, and workflows, that operationalize advanced analytics for spares planning decision-making.
Convert planning challenges into well-scoped product requirements, including user journeys, success metrics, data needs, and rollout plans.
Build self-serve tools that reduce manual effort and scale insights across the organization.
Define and implement the graph data model, covering nodes and edges, ontology or taxonomy, temporal relationships, and metadata.
Represent spares demand, parts, tools, configurations, sites, and operational signals within the graph.
Create ingestion pipelines and data quality checks to keep the graph accurate, explainable, and trusted.
Enable AI and analytics on top of the graph, including graph traversals, similarity search, embeddings, and graph ML patterns for decision support.
Develop predictive models for demand forecasting, including intermittent and long-tail behavior, demand drivers, and planning signals.
Improve inventory planning outcomes by connecting model outputs to actionable recommendations (for example, safety stock, multi-echelon thinking, and service-level tradeoffs).
Partner with subject matter experts to validate model behavior, define guardrails, and ensure outputs are usable and explainable in operational settings.
Implement testing, monitoring, documentation, versioning, and performance practices for maintainable and robust tools.
Establish repeatable deployment patterns (dev/test/prod), model monitoring, and data lineage for enterprise planning environments.
Produce documentation and enablement materials so tools can be adopted beyond technical users.

Requirements

Strong Python skills for data and ML development (pandas/numpy, ML libraries, model evaluation).
Experience developing customer demand prediction models or other operational decision problems.
Solid graph theory foundation, including graph modeling, connectivity, centrality, communities, bipartite or multipartite graphs, and temporal graphs.
Hands-on experience building with a graph database (for example, Neo4j or similar), including schema design, query patterns, and performance considerations.
Familiarity with graph embeddings and/or graph ML concepts (node/edge embeddings, message passing, link prediction, similarity).
Strong SQL and data modeling skills, with ability to build reliable pipelines across large enterprise datasets.
Experience building production services or internal tools (APIs, web apps, dashboards) with an emphasis on usability and maintainability.
Proven ability to work with non-technical stakeholders, translate ambiguous business needs into effective tools, and drive adoption and change management.
Education and experience alignment:
- MS or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, Operations Research, Industrial Engineering, or related quantitative fields; OR
- MS + 3+ years relevant experience; OR
- BS + 5+ years relevant experience in software engineering, ML engineering, or data engineering with demonstrated delivery of production tools.

Technologies

Python, pandas, numpy, SQL
Neo4j
APIs, web apps, dashboards
Embeddings

Benefits

Base Pay Range: $90,400.00 - $132,600.00 Annually
Participation in performance incentive programs
Medical, Dental, Vision, Life insurance
401(K) including company matching
Employee stock purchase program (ESPP)
Student debt assistance
Tuition reimbursement program
Development and career growth opportunities and programs
Financial planning benefits
Wellness benefits including an employee assistance program (EAP)
Paid time off and paid company holidays
Family care and bonding leave
Paid time off (interns are eligible for some of the benefits listed)

Team / Division

The KLA Services team includes Service Sales, Marketing, Spares Supply Chain Management, Field Operations, Engineering, Product Training, Digital Solutions and Analytics, and Technical Product Support.

Preferred Skills (Nice-to-Have)

Supply chain planning experience (service parts, inventory optimization, safety stock, service-level tradeoffs, replenishment and network concepts).
Experience with probabilistic forecasting approaches and intermittent-demand methods.
Knowledge graphs, ontology design, entity resolution, and semantic modeling patterns.
Experience integrating LLMs with structured data (RAG patterns, tool calling, natural-language-to-query workflows) where governance is required.
MLOps and platform experience, including model tracking, CI/CD, monitoring, containers, and scalable compute.

What Success Looks Like (Examples)

Planners answer critical questions faster with less manual wrangling due to reusable graph data and intuitive tools.
Improved forecast quality and earlier detection of demand changes for targeted segments, especially long-tail and intermittent parts, leading to fewer expedites and fewer stockouts.
Reduced avoidable inventory buffers through better segmentation, variability modeling, and decision support tied directly to planning actions.

AI Use Statement

Use of AI, recording tools, or other technologies to generate, suggest, or provide responses during interviews is not permitted unless explicitly approved in advance as part of a reasonable accommodation or invited by the interviewer.

Equal Opportunity Statement

KLA is proud to be an Equal Opportunity Employer and will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

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1mo ago

Machine Learning Engineer

Mariana Minerals Ann Arbor, MI

Ann Arbor, MI

1mo ago Closed

$120k - $180k/yr Full time Ai Ml Artificial Intelligence Engineer

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Mariana Minerals is building machine learning systems that control mineral refining facilities, with a strong focus on reinforcing learning in physically realistic simulators and closing the gap to real plant data. This is an onsite role in Ann Arbor, MI, where your work moves from experimentation to production. The salary range is $120,000 - $180,000 per year.

What you’ll do

Run reinforcement learning experiments in physically realistic simulators of mineral processing operations, then translate results into improved controllers.
Build and refine training environment components, including reward functions, observations, and action logic, with guidance from senior engineers.
Train control models, track and interpret performance, and investigate why a model underperforms.
Close the loop between simulation and reality by comparing model behavior to real plant data and flagging where simulated physics diverge.
Write clean, well-tested code and contribute to the services that deploy models into production.
Partner with process and chemistry experts to understand the unit operations being modeled.

What you bring

2-8+ years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing, or a strong recent graduate with demonstrated project depth.
Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; reinforcement learning experience is a strong plus.
Proficiency in Python and comfort reading and debugging an existing codebase.
Curiosity about physical, industrial systems and willingness to learn chemistry and process engineering from experts who challenge assumptions.
A self-starter who asks good questions, ships, and escalates blockers early.

How the technology is used

The stack uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots, adapted for autonomous, short-interval control of mineral refining circuits. Models adjust operating set points and configurations in real time, optimizing across lithium recovery, reagent consumption, energy intensity, and equipment uptime simultaneously. Training happens in physically realistic simulators of process units, then performance is validated against real plant data before anything is introduced to live equipment.

Why this matters (and why you’ll like it)

We own the projects, generate the data, and close the loop.
Each facility helps make the software smarter, and the next one faster and cheaper.
Mining is one of the last major industrial sectors that hasn’t been rebuilt with modern software.
Your work directly shapes how critical minerals are produced at scale in the coming decades.

Culture at Mariana Minerals

Extreme Ownership – take full responsibility for outcomes and drive toward solutions.
Engineer Out Requirements, then Automate – simplify, optimize, and automate for scale.
Share Your Legos – collaborate openly, share knowledge, and empower each other to build bigger, better solutions.

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Data Jobs in Ann Arbor, MI

Mid-Level AI Engineer

Service Supply Chain AI Engineer

Machine Learning Engineer

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