What You'll Do
In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise.
About the Role
We are seeking an intellectually curious and technically exceptional AI Engineer to join our Applied AI Research organization.
This role is designed for individuals who enjoy moving beyond application of established techniques and are motivated by solving problems that have no obvious solution. The successful candidate will combine strong software engineering fundamentals with expertise in machine learning, statistical algorithms, deep learning, and agentic AI systems to create next-generation intelligence platforms for semiconductor manufacturing and engineering.
Unlike traditional software engineering roles, this position requires a strong research mindset. We are looking for engineers who question assumptions, derive first-principles understanding of problems, conduct systematic experimentation, and translate emerging research into practical business impact.
This role offers a unique opportunity to grow into a future technical and research leader capable of influencing the direction of AI, analytics, and intelligent automation across the organization.
Vision for the Role
Over the next several years, this individual is expected to evolve from an AI engineer into a recognized research leader who:
Shapes the organization's AI strategy through technical innovation.
Drives a culture of experimentation and evidence-based decision making.
Bridges cutting-edge AI research with real-world engineering applications.
Identifies transformational technologies before they become mainstream.
Inspires teams to pursue ambitious technical challenges.
Builds an innovation ecosystem through mentorship, technical leadership, and collaboration.
Key Responsibilities
Applied AI Research
Investigate emerging AI techniques and evaluate their applicability to semiconductor manufacturing and engineering workflows.
Conduct hands-on research in areas such as
Foundation Models
Agentic AI Systems
Scientific Machine Learning
Computer Vision
Reinforcement Learning
Probabilistic Modeling
Knowledge Representation
Multi-Agent Systems
Causal AI
Develop novel approaches for solving difficult engineering and manufacturing problems.
Design rigorous experimental frameworks to validate hypotheses and quantify impact.
Translate research findings into scalable product capabilities.
Statistical Learning & Algorithm Development
Design and develop advanced algorithms utilizing
Bayesian Inference
Probabilistic Graphical Models
Design of Experiments (DOE)
Time-Series Analysis
Optimization Techniques
Causal Inference
Anomaly Detection
Predictive Modeling
Multivariate Statistics
Graph Analytics
Responsibilities include
Creating explainable and scientifically sound models.
Evaluating statistical significance of experimental outcomes.
Building decision-support and autonomous reasoning systems.
Deep Learning & Scientific AI
Develop next-generation deep learning solutions for
Defect Management
Yield Analytics
Manufacturing Optimization
Image Understanding
Pattern Recognition
Engineering Knowledge Discovery
Work with and innovate on
CNNs
Vision Transformers
Multimodal Models
Graph Neural Networks
Self-Supervised Learning
Representation Learning
Foundation Models
Diffusion Architectures
Candidates should be comfortable reading research papers, reproducing published techniques, and identifying opportunities for improvement.
Agentic AI & Intelligent Systems
Develop intelligent autonomous systems capable of
Planning
Reasoning
Tool Usage
Workflow Orchestration
Long-Horizon Goal Achievement
Build sophisticated AI systems using
LangGraph
Semantic Kernel
AutoGen
CrewAI
OpenAI Agent Frameworks
MCP (Model Context Protocol)
Examples include
AI Copilots
Manufacturing Assistants
Engineering Intelligence Platforms
Autonomous Analytics Systems
Knowledge Agents
Software Engineering Excellence
Develop production-grade solutions using
Primary Languages
Python
Modern C++ (C++17/20)
Additional Technologies
PyTorch
Ray
Spark
Kubernetes
Docker
Vector Databases
Graph Databases
The candidate should be able to transform research prototypes into scalable and maintainable products.
Research Leadership Expectations
Although this is an individual contributor role, the candidate is expected to actively contribute to building a research culture.
This includes
Leading technical reading groups.
Reviewing and discussing recent research papers.
Driving internal innovation initiatives.
Mentoring junior engineers on research methodology.
Promoting first-principles thinking.
Encouraging experimentation and hypothesis-driven development.
Establishing engineering rigor around benchmarking and evaluation.
Success is measured not only by feature delivery but also by the advancement of the team's collective technical capability.
Required Qualifications
Education
MS or PhD preferred in
Computer Science
Machine Learning
Artificial Intelligence
Statistics
Applied Mathematics
Electrical Engineering
Related STEM discipline
Experience
Typically
BS + 5 years
OR MS + 3 years
OR PhD
Demonstrated experience in building production AI systems while maintaining strong interest in research and innovation.
Ideal Candidate Profile
The ideal candidate is someone who
Reads research papers for fun.
Questions conventional assumptions.
Enjoys tackling open-ended technical challenges.
Can move seamlessly from theory to implementation.
Has strong mathematical intuition.
Is passionate about creating new knowledge, not merely applying existing solutions.
Wants to become a future Principal Engineer, Distinguished Engineer, or AI Research Leader.
What Success Looks Like After 3-5 Years
This engineer will have
Become a recognized technical authority in AI and analytics.
Influenced the AI roadmap for multiple products.
Originated innovations that materially impact product differentiation.
Built a thriving culture of experimentation and technical excellence.
Mentored the next generation of AI engineers and researchers.
Established KLA as a leader in AI-native semiconductor manufacturing intelligence.
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
About KLA
We provide advanced inspection tools, metrology systems, process solutions, and computational analytics that make electronics possible, tackling complex challenges. From electron and photon optics to machine learning and data analytics, we seek perfection at the most fundamental level of matter in the universe. If you want to make electronics that push industries forward and make the world a better place, join us.
Use of AI Statement
At KLA, our interviews seek to understand your individual skills, problem-solving approach and authentic thinking. To ensure a fair and consistent evaluation, the use of AI, recording tools or other technologies to generate, suggest or provide responses during interviews—whether virtual or in person—is not permitted unless explicitly approved in advance as part of a reasonable accommodation or invited by the interviewer. Use of these tools may interfere with our ability to evaluate your individual qualifications and affect your candidacy. KLA is committed to advancing innovation through responsible AI, and we value candidates who share this mindset.
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.
