Our team develops Next Generation Sequencing (NGS) solutions used by researchers and clinicians worldwide, providing sample-to-answer pipelines with high reliability, speed, and accuracy of results. We develop machine learning solutions across Illumina’s portfolio, from sequencing functions to analysis and interpretation algorithms. DRAGEN, our secondary analysis platform, has industry leading performance and is used for clinical and research work. We also develop algorithms for on-sequencer pipelines including super-resolution, basecalling, denoising. Advanced AI applications drive transformational genetic insights that improve understanding of human biology, cancer and rare disease.
We are seeking an ML Ops engineer to join our team. This role will develop, implement, and optimize data pipelines for ML systems across Illumina’s products, including DRAGEN and high-throughput sequencing systems like Novaseq X, the highest throughput sequencer in the industry. You will collaborate with cross-functional teams (ML, implementation, bioinformatics, optics and imaging, test) to store and process petabytes of highly heterogenous data (images, sequencing output, population data, truth sets, DNA, RNA, multi-omics, variant calls).
Responsibilities:
- Design, develop, and maintain efficient data and feature extraction and training pipelines
- Develop methods for data QC for inputs to model training.
- Build, tune, and optimize machine learning models; collaborate with data scientists to refine data models, design improvements, conduct experiments, and iteratively improve performance.
- Create monitoring dashboards; perform tuning of ML models, scaling solutions for deployment; investigate and resolve performance issues.
- Run experiments to compare models, features, and hyper-parameters; use A/B testing and continuous monitoring to validate and adjust models during development and after deployment.
- Productize implementations as needed on the cloud and local compute, including data pipelines, training & inference pipelines, and pre & post-processing routines.
- Work across teams to ensure seamless integration of data and machine learning workflows in DRAGEN pipelines
- Produce high-quality, maintainable code and participate in peer code reviews to share knowledge and uphold team standards.
- Help with model experiment design for model building,
- Analyze & evaluate model results, automate analysis pipelines
- Hands-on experience working with ML frameworks such as TensorFlow, PyTorch, or similar.
- Solid understanding of ML fundamentals and data-centric techniques for model training, data cleaning, evaluation.
- Experience with cloud platforms (especially AWS) and tools like MLflow, Kubernetes, Docker, Prefect and Airflow.
- Log and analyze ML workflows using MLOps tools such as MLflow or similar platforms.
- Excellent software engineering & Dev Ops skills
- Participate in code reviews for ML ops, training, prediction pipelines
- Contribute to the roadmap of Illumina's core machine learning capabilities.
- Excellent communication skills and the ability to collaborate with cross-functional teams.
Qualifications
- Bachelors or Master’s in Computer Science, Data Science, or a related technical field and 2+ years of industry experience in data engineering, devops, machine learning, or a similar domain (extraordinary applicants with less experience also considered).
- Knowledge of Machine learning and statistical analysis methods and the ability to identify the most suitable solution for the problem
- Knowledge of Machine Learning and statistical concepts including experimental design, hypothesis testing, regression, classification, and clustering
- Experience writing clean, efficient code in Python, participating in code reviews
- Knowledgable in ETL pipeline performance tuning.
- Experience writing optimized SQL Queries to build and analyze datasets
- Familiarity with tools for scalable data engineering, such as Python, React, flask, DevOps
- Some exposure to a modern Cloud Platform, preferably AWS
- Experience with cloud platforms (especially AWS) and tools like Kubernetes, Docker, Prefect and Airflow.
- Ideal - Experience building full ML model lifecycle solutions - from feature engineering to training, validation, deployment and monitoring.
- Ideal - Experience building and deploying complex and scalable machine learning models in production environments
All listed tasks and responsibilities are deemed as essential functions to this position; however, business conditions may require reasonable accommodations for additional tasks and responsibilities.
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 [email protected]. 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. This role is not eligible for visa sponsorship.