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Superluminal Medicines

ML-driven design of candidate small molecules

Staff Engineer - Research Informatics and AI

Backend EngineeringConfirmed live in the last 24 hours
Full-timeBoston, MA, USAIn-person

About the Job

Requirements

  • A bachelor's degree in Software Engineering, Computer Science, Information Technology, or a related field, or equivalent professional experience.
  • At least 5 years of professional software engineering experience building and operating production systems.
  • At least 3 years of Python experience designing maintainable and well-tested software.
  • Experience building systems that integrate data across APIs, databases, files, asynchronous processes, and third-party platforms.
  • Experience with containers and modern deployment patterns using Docker and Kubernetes.
  • Experience designing scalable software architecture and making technical design decisions.
  • Experience designing and consuming REST APIs.
  • Experience developing production systems on Google Cloud Platform and cloud-native architecture.
  • Experience writing SQL queries, designing relational data models, and developing production data pipelines or workflows.
  • Experience developing and operating production software using automated testing, CI/CD pipelines, application monitoring, logging, and incident troubleshooting practices.

Responsibilities

  • Design, build, and operate production software systems supporting scientific data and wet lab workflows.
  • Own the architecture and implementation of systems for compound registration, experimental data ingestion, validation, transformation, and publishing.
  • Build reliable integrations across internal applications, APIs, cloud services, databases, and third-party scientific platforms.
  • Develop backend services, data pipelines, and internal applications used directly by scientists and research teams.
  • Design systems that are observable, testable, resilient, and maintainable as scientific workflows and data volumes scale.
  • Work directly with scientists to understand operational problems, identify root causes, and translate ambiguous workflows into clear technical solutions.
  • Improve data quality and system reliability through validation frameworks, automated testing, monitoring, and well-defined interfaces.
  • Establish engineering practices around code quality, CI/CD, deployment, documentation, and operational ownership.

Desired Qualifications

  • At least 8 years of professional software engineering experience building and operating production systems.
  • Experience in biotechnology, pharmaceuticals, life sciences, or another technically complex scientific environment.
  • Experience with LIMS, ELNs, compound registration systems, laboratory informatics, inventory platforms, or scientific instruments.
  • Experience with drug discovery data, including compounds, assays, experimental results, and scientific metadata.
  • Experience with BigQuery, dbt, Dagster, or similar modern data platforms and orchestration tools.
  • Experience building internal tools or user-facing applications for technical users.
  • Experience with scientific Python, cheminformatics, or bioinformatics workflows.
  • Experience with infrastructure-as-code and cloud security best practices.
  • Experience modernizing manual, fragmented, or vendor-dependent operational workflows.

About the Company

Superluminal Medicines

ML-driven design of candidate small molecules

Superluminal Medicines develops small-molecule drug discovery solutions by combining deep biology, chemistry, and machine learning. It creates candidate-ready compounds with high speed and accuracy, using a proprietary big data platform and predictive design models to model protein shapes and design selective compounds that induce precise structural changes for therapeutic effects. The company collaborates with pharmaceutical and biotech firms, licensing its technology and pursuing milestone-based payments, rather than selling products outright. This partnership-centric model helps clients accelerate their drug discovery programs in a highly competitive market. The company aims to shorten the path from target to clinical candidate by delivering well-characterized, selective small molecules efficiently.

Company size
51-200
Company stage
Series B
Total funding
$213M
Headquarters
Boston, MA
Founded
2023

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