Senior Software Engineer, Data

About the role

Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Data Platform Team (Data).

Responsibilities

• Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.
• Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Leverage AWS services, Kubernetes, and modern DevOps practices to build and deploy production-grade systems at scale.
• Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5-8+ years of engineering experience building and deploying large-scale backend systems in production.
• Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).
• Experience with orchestration systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic).
• Experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.

Qualifications

• Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware.

Skills

• Python for Science.

Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• U.S. Benefits: Medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
• International Benefits: Comprehensive benefits program tailored to your region.

Pay

• USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Schedule

• Full-time position.