Senior Backend Engineer - Robotics Data & Scheduling

Socket.dev; Cambridge (MA); On-site; USD 144,000 - 240,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

Employer-paid life and disability

Flexible time off

Paid parental leave

Educational assistance

Commuter benefits

Lunch program

Job summary

Lila Sciences is recruiting a senior back-end engineer to build the data foundations for autonomous lab scheduling and digital twin models. You will own the core services used by scientists, operators, and engineers to run robots efficiently and trust their data.

In this role, you will design durable scheduling systems, implement digital twins, and manage data pipelines that turn instrument output into governed, queryable data, enabling data science and capacity planning at scale.

Qualifications

• 4–8 years of back-end engineering experience.
• Production services in Python (FastAPI) at scale.
• Data engineering experience with workflow orchestration.
• Hands-on SQL (PostgreSQL) and object storage (S3).
• Cloud-native delivery with containers, IaC, and CI/CD.
• End-to-end ownership from design to delivery and reliability.

Responsibilities

• Design scheduling systems for experiments across autonomous labs.
• Model digital twins and data layer to predict factory behavior.
• Own Flyte pipelines, S3 lakehouse, and PostgreSQL models for governed data.
• Enable data science with batch and event-driven pipelines.
• Deliver capacity planning with customer-facing services.
• Operate at scale on AWS EKS with Terraform and GitHub Actions.

Skills

Python FastAPI

Data engineering

SQL PostgreSQL

Cloud AWS

Flyte Temporal

Docker ECR

Terraform

GitHub Actions

End-to-end ownership

Collaboration

Tools

Flyte

Temporal

PostgreSQL

S3

AWS EKS

Terraform

GitHub Actions

Docker

Job description

Lila Sciences is recruiting a senior back-end engineer to build the data foundations for autonomous lab scheduling and digital twin models. You will own the core services used by scientists, operators, and engineers to run robots efficiently and trust their data.

In this role, you will design durable scheduling systems, implement digital twins, and manage data pipelines that turn instrument output into governed, queryable data, enabling data science and capacity planning at scale.