Company Overview
Group/Division
Job Description/Preferred Qualifications
Our Enterprise Analytics team is at the forefront of transforming data into actionable insights that drive strategic decisions across the organization. We are a collaborative, cross-functional group of engineers, data scientists, analysts, and architects who value:
Innovation: We embrace new technologies and encourage experimentation to solve complex business problems.
Ownership: Every team member is empowered to take initiative and drive projects from concept to production.
Transparency: We foster open communication, regular knowledge sharing, and inclusive decision-making.
Continuous Learning: We support professional development through certifications, tech talks, and hands-on learning.
Impact: Our work directly influences enterprise-wide initiatives, from customer experience to operational efficiency.
You’ll be joining a team that believes in building with purpose, where engineering excellence meets data-driven strategy.
Key Responsibilities
- Design and deliver LLM-powered applications such as:
- Retrieval-Augmented Generation (RAG) with enterprise knowledge sources
- Agentic workflows (tool/function calling, orchestration, multi-step reasoning)
- Text extraction/summarization, classification, Q&A, and document intelligence
- Build and optimize retrieval pipelines: chunking strategies, embeddings, vector search, reranking, grounding, and evaluation.
- Create robust evaluation frameworks: golden datasets, automated scoring, offline/online A/B testing, and continuous regression testing for prompts/models.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- 6+ years experience in software engineering, ML engineering, or applied AI roles.
- Strong programming expertise in Python, solid SQL, and strong software engineering fundamentals (APIs, testing, CI/CD, code quality).
- Demonstrated experience building and deploying AI/ML systems into production with measurable outcomes.
- Hands-on experience building LLM applications (RAG/agents/tool calling) and implementing evaluation/monitoring practices.
- Experience with vector databases / search (e.g., Azure AI Search or equivalent), rerankers, and embedding lifecycle management.
- Familiarity with Responsible AI practices: privacy, security reviews, model risk management, bias/fairness, and explainability.
Core Technical Skills
- LLM Apps: RAG, agents, tool/function calling, prompt engineering, evaluation harnesses, guardrails
- Languages: Python (required), SQL (required)
- Cloud: Azure (deployments, security, observability, CI/CD)
- Ops: Monitoring, incident response, SLO/SLA management, cost optimization
- Data: ETL/ELT, distributed processing concepts, data quality frameworks
Minimum Qualifications
Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years
We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.
KLA is proud to be an equal opportunity employer
Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA’s Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to [email protected] to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.
Skills Required
- Bachelor's degree in Computer Science, Engineering, or related field
- 6+ years experience in software engineering, ML engineering, or applied AI roles
- Strong programming expertise in Python
- Solid SQL skills
- Experience building and deploying AI/ML systems
- Hands-on experience with LLM applications
KLA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about KLA and has not been reviewed or approved by KLA.
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Retirement Support — Retirement offerings include a 401(k) plan with company matching and financial planning support. Student debt assistance and related financial benefits reinforce long-term savings and security.
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Equity Value & Accessibility — Ownership programs include an Employee Stock Purchase Plan and broad-based RSU participation that extend equity beyond a narrow group. These elements complement competitive pay and bonuses to strengthen total rewards.
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Leave & Time Off Breadth — Time-off programs span paid time off, paid company holidays, and paid volunteer time. Family care and bonding leave and back-up care services add flexibility during life events.
KLA Insights
What We Do
KLA develops industry-leading equipment and services that enable innovation throughout the electronics industry. We provide advanced process control and process-enabling solutions for manufacturing wafers and reticles. In close collaboration with leading customers across the globe, our expert teams of physicists, engineers, data scientists and problem-solvers design solutions that move the world forward.








