Senior Software Engineer

Summary

Join Domino Data Lab's Life Sciences Team and revolutionize the delivery of transformative therapies. In this software engineering role, you will enhance Domino Datasets functionality, improve Git repository support, design regulatory compliance features, build audit logging, automate data version tracking, and optimize workspace performance. You will leverage your expertise in scalable systems, API development, performance optimization, testing, and distributed computing. The ideal candidate possesses 5+ years of experience in a software engineering role and proficiency in back-end programming languages. Domino offers a competitive salary, equity, bonuses, 401(k), and comprehensive health benefits.

Requirements

• 5+ years previously in a software engineering individual contributor role
• Developing and managing high-performance back-end systems in distributed compute environments
• Integrating back-end systems with front-end interfaces and third-party services
• Designing secure, efficient APIs using technologies like RESTful APIs and gRPC
• Profiling and fine-tuning back-end systems, particularly in cloud environments and with container technologies like Docker and Kubernetes
• Implementing robust testing frameworks (unit, integration, end-to-end) and maintaining CI/CD pipelines
• Familiarity with frameworks like Apache Hadoop, Spark, Ray, or similar technologies
• Proficiency in languages like Python, Java, Scala, or Go to build scalable web services
• Experience with service-oriented architectures (SOA) and modular, maintainable system design

Responsibilities

• Enhance Domino Datasets functionality to allow access via APIs, complementing traditional file system mounts
• Improve Git repository and version control support within Domino Projects and Workspaces
• Design and implement regulatory compliance features aligned with FDA requirements, ensuring the authenticity, confidentiality, and validation of electronic records
• Build end-to-end audit logging to provide comprehensive workflow transparency
• Automate external data version tracking to improve lineage and reproducibility for third-party data sources
• Optimize workspace performance, focusing on Kubernetes-based compute-on-demand IDE functionality

Preferred Qualifications

Knowledge of machine learning workflows and infrastructure

Benefits

• Equity
• Company bonus or sales commissions/bonuses
• 401(k) plan
• Medical, dental, and vision benefits
• Wellness stipends