Software Engineer - Machine Learning

Base Pay Range: $94,400.00 - $160,500.00 Annually Primary Location: USA-MI-Ann Arbor-KLA KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits identified below. Interns are eligible for some of the benefits identified below. Our pay ranges are determined by role, level, and location. The range displayed above reflects the minimum and maximum pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including location, job-related skills, experience, and relevant education level or training. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process. 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. The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.

• Understand the data in the context of the business and assess technologies that can be demonstrated to generate useful and actionable insights
• Develop technology solutions in the field of predictive analytics, anomaly detection, classification and/or regression problems, ML/DL model architecture, statistical modeling, time series, feature engineering, etc.
• Quickly build a proof-of-concept machine learning pipeline from data collection, model training, to metrics to evaluate the efficiency of the proposed methodology
• Build a machine learning platform/application for the end-to-end machine learning lifecycle: rapid prototyping; full-scale training; deploying, monitoring, maintaining models; and iterating on modeling ideas based on user feedback
• Serve the machine learning model in a stand-alone application or through a robust API
• Collaborate with business to understand their requirements, collect their feedback on machine learning results, and incorporate various signals into the machine learning models

• Bachelor's degree in Computer Science, Computer Engineering or related field
• Minimum five (5) years of relevant experience in Machine Learning and Machine Learning Modeling
• Understanding of all well-known machine learning algorithms. The candidate should know the assumptions, advantages, limitations of each model and grasp the trade-off when choosing among different models
• Proficiency in programming languages such as Python, R, Java, and C/C++
• Hands-on experience with building machine learning models using Scikit-learn, Tensorflow, Keras or PyTorch
• Strong core CS fundamentals (data structures, algorithms, architecting systems)
• Practical experience with implementing a machine learning system that may mix with heuristic rules, prior knowledge, and other constraints
• Ability to solve problems independently, good sense of collaboration and interpersonal skills

• Experience with developing GenAI framework for RAG, GraphRAG, fine-tuning LLM, etc.
• Experience with large-scale data processing and distributed computing
• Understanding of front-end application development