Service Supply Chain AI Engineer

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.