Software Gigs

As a Data Developer, you will design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data platforms that integrate enterprise systems and support AI/ML initiatives for the U.S. Navy. You will perform data engineering tasks including cleansing, transformation, and optimization of SQL and Apache Spark workloads on AWS, while also developing predictive models and generative AI solutions using Python-based technologies. You will build interactive dashboards and visualizations in Tableau or Qlik, translating technical findings into actionable insights for stakeholders. An active Secret clearance, U.S. citizenship, and a bachelor's degree in a technical field (or 4+ years of relevant professional experience) are required.

Design and implement software integrations connecting lab automation infrastructure (liquid handlers, plate readers, robotic workstations, analytical instruments) with orchestration layers and digital workflows. Build production-grade Python applications and containerized services using Docker and Kubernetes, deploy CI/CD pipelines, and maintain LIMS integrations. Explore AI-driven decision-making and autonomous orchestration capabilities, staying current with LLM tooling and agent frameworks. Provide technical leadership and mentorship to the automation engineering team while shaping the roadmap for closed-loop autonomous discovery systems.

Join Singular Genomics' core software team as a generalist Software Engineer contributing to the sequencing analysis pipeline, operational tooling, and field support. You'll work across Python development, CI/CD infrastructure (Jenkins, Bitbucket), HPC job execution, and diagnostic troubleshooting of production failures on genomic sequencers. Responsibilities include pipeline bug fixes and features, build system maintenance, field triage, data handling logic, and developing lightweight web services and internal APIs. You need 2–5 years of professional experience, solid Python fundamentals, Linux/HPC familiarity, and the ability to debug and move fast across a large, real production codebase.