Software Engineer - Machine Learning

$94,400 - $160,500/Yr

Unclassified - Ann Arbor, MI

Full-time - Mid Level

Ann Arbor, MI

About the position

KLA is seeking a dedicated and motivated Software Engineer to join our Information Technology (IT) group, which plays a crucial role in the global business by connecting people, processes, and technology. The Software Engineer will be instrumental in the development and implementation of Machine Learning (ML) and Generative AI (GenAI) solutions that facilitate predictive modeling and data-driven decision-making. This position requires a strong background in statistics and programming, along with a deep understanding of data science and software engineering principles. The successful candidate will collaborate with multi-functional teams to deploy scalable ML and software solutions that drive innovation and strategic insights for our business partners. In this role, the Software Engineer will be responsible for understanding the data in the context of the business and assessing technologies that can generate useful and actionable insights. The candidate will develop technology solutions in predictive analytics, anomaly detection, classification, regression problems, ML and deep learning model architecture, statistical modeling, time series analysis, and feature engineering. The role involves quickly building proof-of-concept machine learning pipelines from data collection to model training, as well as evaluating the efficiency of proposed methodologies. Additionally, the Software Engineer will build a machine learning platform/application for the end-to-end machine learning lifecycle, which includes rapid prototyping, full-scale training, deploying, monitoring, maintaining models, and iterating on modeling ideas based on user feedback. The candidate will also serve the machine learning model in a stand-alone application or through a robust API, collaborating with business stakeholders to understand their requirements, collect feedback on machine learning results, and incorporate various signals into the machine learning models. This position offers an exciting opportunity to work in a dynamic environment where innovation is at the forefront, and employees are encouraged to tackle challenging problems.

Responsibilities

• Understand the data in the context of the business and assess technologies that can generate useful and actionable insights.
• Develop technology solutions in predictive analytics, anomaly detection, classification, 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.

Requirements

• 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, including their assumptions, advantages, limitations, and trade-offs.
• 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.

Nice-to-haves

• 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.

Benefits

• 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.
• Family care and bonding leave.