Summary
Our client, an innovative scientific research company developing automation and data tools that power next-generation AI-driven scientific platforms, is looking for a Senior Backend Engineer – Data & Infrastructure to help design, optimize, and scale integrations that bridge laboratory workflows with AI-driven experimentation and analysis.
This role combines backend engineering, data architecture, and cloud infrastructure to build scalable systems that connect lab robotics, data pipelines, and user-facing tools.
If you’re passionate about designing robust APIs, building efficient data systems, and enabling scientists through powerful yet intuitive interfaces, this opportunity is for you. You’ll work on creating integrations that allow both humans and AI agents to track, analyze, and optimize experiments in real time.
Responsibilities:
- Database Architecture & Design
Design, implement, and optimize relational database schemas to support labware tracking at well-level resolution, ensuring scalability, indexing efficiency, and data integrity. - Backend Development for Data & ML Enablement
Build APIs and backend services in Python to enable seamless access to structured data for internal applications, laboratory processes, and Machine Learning workflows. - Data Pipelines & ETL Engineering
Develop and maintain ETL pipelines using Airflow or Spark to collect, transform, and prepare laboratory data for analytics, reporting, and ML model consumption. - Temporary Data Structures for ML Processing
Design and manage temporary data storage (temp flags, staging tables) to support model-in-the-loop operations and batch processing. - Cloud Deployment & Infrastructure (AWS)
Autonomously deploy, monitor, and maintain services and database systems in AWS, ensuring reliability, performance, and security. - Cross-functional Collaboration
Collaborate closely with data scientists, ML engineers, hardware specialists, and researchers to understand data requirements and deliver cohesive technical solutions.