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 collaborate with product and software development teams to deploy machine learning models to users.
- Execution of small to medium scale project scope, including ownership of all deliverables, with guidance.
- Able to take on additional tasks or responsibilities when required.
- Develop solutions to restore and sustain optimal functionality of biopharmaceuticals manufacturing equipment and systems with some guidance.
- Incident investigation and reporting:
- Participate or lead cross functional investigation team with some supervision.
- Mentor team members on good investigation & reporting skills.
- Adapt different techniques and concepts in technical writing for effective engagement with individuals and/or teams.
Listed responsibilities are an essential, but not exhaustive list, of the usual duties associated with the position. Changes to individual responsibilities may occur due to business needs.
Position Requirements:
- Minimum bachelor’s degree with 2~3 years of experience in using statistical modeling tools to analyze and improve yield and equipment performance or data science roles.
- Complete tasks in a safe and efficient manner.
- Able to undergo job rotation/ cross training.
- Meticulous, keen attention to details and organized.
- Strong cross functional team player.
- High fluency in spoken and written English and presentation skills.
- Ensure compliance with cGMP, Quality, work safety instructions & practices at all times.
- Ability to work independently as well as collaboratively as part of a highly-skilled team.
- Good communication skills possess logical and analytical skills with attention to detail.
- High level of discipline and integrity.
- Able to undertake multiple tasks.
- Possess a positive attitude and sense of urgency.
All listed requirements are deemed as essential functions to this position; however, business conditions may require reasonable accommodations for additional task and responsibilities.
Preferred Experience/Education/Skills:
- Bachelor’s degree or equivalent in Computer Science, Mathematics, Statistics, Engineering or related discipline preferred, Master’s degree will have added advantage.
- Practical knowledge of machine-learning techniques, including time-series analysis, anomaly detection, natural language processing and/or computer vision
- Practical experience in PLC programming and troubleshooting on Siemens, Rockwell/Allen-Bradley, Beckhoff, or equivalent platforms.
- Working knowledge of SQL, databases, APIs, software testing, system integration and source-control tools such as Git
- Understanding of industrial communications, equipment data acquisition, SCADA/historian systems, and OT architecture concepts.
- Proficiency in Python or R, experience with C# and JavaScript will be added advantages.
- Familiarity with one or more deep learning frameworks, such as Keras, TensorFlow, PyTorch, etc.
- Knowledge of Statistical tools such as JMP, Minitab etc.
- Knowledge of data visualization tools such as matplotlib, seaborn, plotly, etc.
- Strong analytical and quantitative problem-solving ability.
- Excellent communication, interpersonal relationship skills and a strong team player.
- Experience with Cloud computing, containerization and data warehouse will be added advantage.
We are a company deeply rooted in belonging, promoting an inclusive environment where employees feel valued and empowered to contribute to our mission. Built on a strong foundation, Illumina has always prioritized openness, collaboration, and seeking alternative perspectives to propel innovation in genomics. We are proud to confirm a zero-net gap in pay, regardless of gender, ethnicity, or race. We also have several Employee Resource Groups (ERG) that deliver career development experiences, increase cultural awareness, and offer opportunities to engage in social responsibility. We are proud to be an equal opportunity employer committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status, and genetic information. Illumina conducts background checks on applicants for whom a conditional offer of employment has been made. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable local, state, and federal laws. Background check results may potentially result in the withdrawal of a conditional offer of employment. The background check process and any decisions made as a result shall be made in accordance with all applicable local, state, and federal laws. Illumina prohibits the use of generative artificial intelligence (AI) in the application and interview process. If you require accommodation to complete the application or interview process, please contact accommodations@illumina.com. To learn more, visit: https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf. The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants.
