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Company Overview
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice\-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R\&D. Our expert teams of physicists, engineers, data scientists and problem\-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.
Job Description/Preferred Qualifications
Sr. Technical Solutions Managers are core to KLA’s technology, while we do not currently have an opening, we are always building our Technical Solutions Manager talent community, we are interested in learning about your background.
Apply to this posting for Future Opportunities with KLA.
KLA is seeking a Sr. Technical Solutions Manager to drive the market strategy and growth of Fault Detection and Classification (FDC), Virtual Metrology (VM), and AI\-powered Yield Enhancement software solutions.
This is a highly visible Staff\-level role at the forefront of semiconductor digital transformation. You will help define how leading manufacturers leverage AI, machine learning, advanced analytics, and factory intelligence to improve yield, accelerate ramp, and optimize production. Working across some of the industry's most advanced fabs, you will shape the future of data\-driven semiconductor manufacturing while influencing strategic growth for one of KLA's fastest\-growing software businesses.
Position Summary
The Technical Solutions Manager will serve as the market and business leader responsible for driving product positioning, go\-to\-market strategy, customer engagement, and portfolio growth for KLA's software solutions focused on:
- Fault Detection \& Classification (FDC)
- Virtual Metrology (VM)
- Advanced Process Control (APC) integrations
- Yield Analytics
- Manufacturing Intelligence
- AI/ML\-Driven Process Optimization
This role requires a unique blend of semiconductor manufacturing expertise, software product marketing experience, business strategy, and data analytics knowledge. The successful candidate will work closely with customers, product management, engineering, sales, and executive leadership to define market direction and accelerate adoption of AI\-enabled manufacturing solutions.
Key Responsibilities
Market Strategy \& Thought Leadership
- Develop and execute long\-term product marketing strategies for KLA's FDC, Virtual Metrology, and Yield Enhancement software portfolio.
- Analyze semiconductor manufacturing trends, Smart Factory initiatives, Industry 4\.0 adoption, and AI\-driven process optimization opportunities.
- Assess market dynamics, customer needs, and competitive landscapes to identify growth opportunities.
- Provide strategic recommendations that influence product investment priorities and business planning.
Product Positioning \& Messaging
- Define compelling value propositions that clearly communicate customer benefits including yield improvement, cycle\-time reduction, process optimization, and productivity gains.
- Develop product messaging, positioning frameworks, and competitive differentiation strategies.
- Create executive\-level presentations, customer\-facing content, white papers, web content, customer success stories, and product launch materials.
- Translate complex AI, analytics, and process control capabilities into clear business outcomes.
Customer \& Industry Engagement
- Engage directly with semiconductor manufacturers, foundries, IDMs, memory customers, and OSATs to understand emerging manufacturing challenges.
- Conduct Voice of Customer (VoC) initiatives to identify unmet market needs and solution opportunities.
- Lead customer advisory discussions and participate in strategic account engagements.
- Represent KLA at industry conferences, customer workshops, and technical forums.
Product \& Portfolio Leadership
- Partner closely with Product Management, Engineering, Applications, and Data Science teams to align product strategy with customer requirements.
- Influence software roadmaps based on market intelligence and customer feedback.
- Assist in defining product packaging, pricing, and commercial strategies.
- Support business case development for new product investments and market expansion opportunities.
Sales Enablement \& Revenue Growth
- Equip field sales, applications, and business development teams with effective messaging, competitive insights, and technical sales tools.
- Develop sales training programs and customer engagement materials.
- Support strategic opportunities and executive\-level customer presentations.
- Monitor market performance, adoption metrics, and competitive activity to drive growth initiatives.
Required Qualifications
- Bachelor's degree in Engineering, Computer Science, Data Science, Physics, Mathematics, Semiconductor Manufacturing, Business, or related field.
- 10\+ years of experience in product marketing, product management, semiconductor manufacturing, yield engineering, process control, manufacturing software, or related technical\-commercial roles.
- Strong understanding of semiconductor manufacturing operations and process control methodologies.
- Familiarity with:
+ Fault Detection \& Classification (FDC)
+ Virtual Metrology (VM)
+ Statistical Process Control (SPC)
+ Advanced Process Control (APC)
+ Yield Management Systems
+ Manufacturing Analytics Platforms
- Experience marketing or supporting software products and data\-driven solutions.
- Proven ability to translate technical capabilities into business value propositions.
- Excellent communication, presentation, and stakeholder management skills.
- Demonstrated success influencing cross\-functional teams without direct authority.
Preferred Qualifications
- Master's degree, MBA, or PhD in a technical discipline.
- Experience with semiconductor foundries, memory manufacturers, logic fabs operations.
- Knowledge of Artificial Intelligence (AI), Machine Learning (ML), Predictive Analytics, Digital Twin technologies, or Smart Manufacturing initiatives.
- Experience with manufacturing data architectures, MES systems, APC ecosystems, and factory automation environments.
- Familiarity with semiconductor process modules including lithography, etch, deposition, CMP, metrology, and inspection.
- Experience launching enterprise software, SaaS platforms, or manufacturing intelligence solutions.
Key Competencies
Strategic \& Business Leadership
- Market Strategy Development
- Portfolio Growth Planning
- Business Case Development
- Competitive Intelligence
- Revenue Growth Initiatives
Technical Expertise
- Semiconductor Process Control
- Fault Detection \& Classification
- Virtual Metrology
- Yield Analytics
- AI \& Machine Learning Applications
- Smart Manufacturing
Customer \& Commercial Excellence
- Customer Engagement
- Executive Presentations
- Consultative Selling
- Product Positioning
- Go\-to\-Market Execution
Leadership \& Collaboration
- Cross\-Functional Influence
- Strategic Communication
- Change Leadership
- Global Collaboration
- Stakeholder Management
Minimum Qualifications
Doctorate (Academic) Degree and related work experience of 3 years; Master's Level Degree and related work experience of 6 years; Bachelor's Level Degree and related work experience of 8 years
Base Pay Range: $138,500\.00 \- $235,500\.00
Primary Location: USA\-CA\-Milpitas\-KLA
KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 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, and family care and bonding leave.
Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job\-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.
KLA is proud to be an Equal Opportunity Employer. We 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. Please contact us at [email protected] or at \+1\-408\-352\-2808 to request accommodation.
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.
Salary Context
This $138K-$235K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At KLA, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($187K) sits 15% below the category median. Disclosed range: $138K to $235K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
KLA AI Hiring
KLA has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Research Scientist. Positions span Milpitas, CA, US, Ann Arbor, MI, US. Compensation range: $188K - $235K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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