JOB SUMMARY
We are seeking a Senior Software Backend Engineer, Platform Computing to integrate and operate the compute layer that powers data processing and model inference across Iambic's drug discovery platform.
You will work within the Software Platform team, partnering with ML engineers and scientists to ensure production workloads are reliable, performant, and scalable. Your focus will be on integrating and operating compute infrastructure and orchestration systems that enable scientific workflows across the platform. This position will be based at our San Diego Headquarters.
KEY RESPONSIBILITIES
- Integrate and maintain the compute layer supporting data processing and model inference workflows in production
- Ensure reliable and performant execution of workloads through monitoring, troubleshooting, and failure resolution
- Operate and extend workflow orchestration systems (e.g., Prefect, Coiled, Modal or similar frameworks)
- Support deployment and execution of ML model outputs in production environments
- Enable scientific workflows by integrating external data sources and supporting analysis and inference workloads within and outside of Insight (e.g., large-scale assay refits)
- Collaborate with ML engineers and cross-functional teams to translate model capabilities into production-ready systems
- Integrate new compute capabilities into the platform as they are developed, ensuring scalability and flexibility
- Establish and maintain best practices for reliability, observability, and operational support
QUALIFICATIONS
- 10+ years of relevant experience with a Bachelor's degree; or 8 years and a Master's degree; or equivalent experience
- Strong software engineering skills with proficiency in Python
- Experience integrating and operating distributed or cloud-based systems in production
- Familiarity with workflow orchestration frameworks (e.g., Prefect, Modal, Coiled, Airflow or similar)
- Experience supporting data processing or compute-intensive workloads, including troubleshooting and performance optimization
- Familiarity with containerization and deployment patterns (e.g., Docker, Kubernetes)
- Solid understanding of cloud infrastructure (AWS preferred), including compute, networking, and storage
- Ability to collaborate effectively with ML engineers to operationalize model outputs (e.g., working with PyTorch, Hugging Face, or similar frameworks at the integration level)
- Experience working with data-intensive or scientific workflows is a plus
- Demonstrates strong engineering rigor, including testing, version control, code quality, and observability practices
PAY AND BENEFITS
We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team. We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.
