Manufacturing Equipment Engineer 2 (Operations Intelligence)

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Position Summary As an Equipment Engineer 2 (Operations Intelligence) at our Manufacturing organization, you will be working on multi-disciplinary projects, collaborating with a team of software engineers, process, equipment, manufacturing/product development engineers to develop new data science solutions/models/analytics to improve quality, improve yield, reduce variations, improve manufacturing cycle time, reduce cost, and extend manufacturing capabilities from data in-sights. You are also required to constantly learn/explore new front tier technology and innovatively apply/deliver solutions to Manufacturing operation. Position Responsibilities: Complete required training (e.g. cGMP, safety and work instructions, etc.) within a stipulated time frame. Execute tasks strictly following cGMP, Quality, Safety and Work instruction requirements. Ensure employees follow safety, quality requirement, and all applicable company policies at all times. Develop, troubleshoot and support PLC/HMI-based equipment controls, sensors and industrial communication interfaces Partner with Operations Technology and Automation teams to connect equipment data using applicable protocols such as OPC UA, MQTT, Modbus, Ethernet/IP, Profinet, or SECS/GEM. Develop and sustain equipment tag mapping, contextualization, databases, APIs, and scalable data pipelines for operational intelligence use cases. Develop operational dashboards, equipment health indicators, condition-monitoring rules, and escalation workflows. Apply statistical analysis, time-series methods, and machine-learning techniques to equipment anomaly detection, diagnostics, and performance improvement. Support AI-assisted troubleshooting and knowledge-retrieval solutions within defined human-review and governance controls. Lead or support equipment criticality assessments, FMEA, RCA, incident investigations, and transition from time-based to usage- or condition-based maintenance where justified. Develop models related to time series analysis / computer vision / natural language processing on manufacturing related datasets to address various business problems of clients through leveraging advanced statistical modeling, machine learning, or data mining techniques with some supervision. Communicate and…