Ml/software Engineer

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.

Deep Learning/AI Engineer 1 - Singapore

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.

Illumina believes that everyone has the ability to make an impact, and 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, m