lims jobs in San Diego

Develop and execute automated test suites in Python to validate genomics and bioinformatics applications, including sequencing workflows, variant-calling results, and sample-to-result traceability. Test integrations with Laboratory Information Management Systems (LIMS), perform functional, integration, regression, and end-to-end testing, and integrate automated tests into CI/CD pipelines.…See more Collaborate with wet lab and dry lab teams to translate scientific requirements into test scenarios, validate data integrity and audit trails, and partner with engineering teams on defect resolution. Requires a degree in Computer Science, Bioinformatics, or Life Sciences, 3+ years of QA/test automation experience, strong Python skills, and working knowledge of genomics concepts and laboratory workflows.

Automation QA Engineer for a genomics/bioinformatics project in San Diego. The role requires 3+ years of QA/test automation experience with Python, developing and maintaining automated test suites using pytest, unittest, or Robot Framework.…See more Responsibilities include functional, integration, and regression testing of genomics and sequencing software; validating NGS data and sample-to-result traceability; testing LIMS integrations and laboratory workflows; and collaborating with wet-lab and dry-lab teams to create real-world test scenarios. Knowledge of NGS, LIMS, bioinformatics, and life-sciences compliance is highly valuable.

Provide IT infrastructure, application, and technical support for laboratory environments in life sciences/pharmaceutical/biotechnology settings. Install, configure, maintain, and troubleshoot laboratory IT systems including LIMS, ELN, LES, CDS applications, laboratory instruments, Windows servers, Active Directory, and networking.…See more Support GxP-regulated environments, system validation, change control, and audit activities while ensuring security, availability, and data integrity.

This is a senior full-stack engineer role responsible for architecting and building internal platforms and cloud infrastructure that serve operations, finance, lab, and external customers. The engineer will design data models and APIs connecting lab systems, business software (NetSuite, ATS, CRM), and internal dashboards; build robust cloud infrastructure managing provisioning, cost, reliability, and security; and set technical direction on architecture, code quality, CI/CD, and observability across a growing engineering org.…See more The role requires 10+ years of full-stack production experience, deep hands-on cloud infrastructure knowledge, modern frontend (React) and backend skills, and ability to work directly with non-engineering stakeholders to translate ambiguous business requirements into shipped software. Over time, the engineer will build and mentor a team.

Design and develop software applications that orchestrate complex automated laboratory workflows and closed-loop learning systems for biotherapeutics discovery. Build data pipelines, visualization tools, and machine learning models for visual inspection, predictive maintenance, and process optimization.…See more Implement IoT integrations, digital lab twins, telemetry systems, and maintain integrations across automation schedulers, LIMS, and data platforms using DevOps best practices and cloud solutions. Requires a Ph.D. in Computer Science, Software Engineering, or Bioengineering with 3+ years of industry experience (or equivalent M.S./B.S. with 10+/13+ years respectively), strong proficiency in Python, SQL, and JavaScript, and experience with lab digitalization and autonomous systems.

This role combines software engineering leadership with lab automation integration and early-stage AI prototyping. You will own the translation layer between high-level workflow logic and low-level instrument control, deploy and maintain containerized services using Docker and Kubernetes with CI/CD practices, and build scalable Python applications connecting experimental readouts with downstream analysis tools.…See more You'll collaborate on incorporating AI-driven decision-making into automation workflows, mentor the automation engineering team, and help shape the technical roadmap for autonomous discovery systems.

Staff Software Engineer to own end-to-end LIMS (Laboratory Information Management System) implementation for a clinical/molecular diagnostics lab, connecting sample tracking to lab automation and instrumentation. Responsibilities include building the LIMS platform, creating integrations between LIMS and lab devices, modeling complex sample preparation and assay execution data chains, and ensuring compliance with 21 CFR Part 11.…See more Requires 7+ years of hands-on LIMS experience in clinical or molecular diagnostics, deep knowledge of sample-tracking data models for high-throughput workflows, full-stack programming across UI/APIs/backend, and regulated-environment expertise (21 CFR Part 11, ISO standards, CAP/CLIA). This is a hands-on technical leadership role requiring strong communication between lab scientists, automation engineers, and software teams.

Principal Engineer leading the design, build, and operation of an enterprise data platform serving 50+ source systems across R&D, Commercial, Manufacturing, and other business functions. The role combines hands-on data engineering (PySpark, T-SQL, Python, Data Factory, medallion architecture) with technical leadership of data engineers, vendor management, platform standards enforcement, and cross-functional stakeholder partnership.…See more Responsibilities span CI/CD pipeline design, data quality and reliability instrumentation, semantic layer development, data governance implementation, and delivery of new source-system integrations at scale.

Develop and execute comprehensive automated test plans, test cases, and regression suites for genomics and bioinformatics software applications. Perform functional, integration, regression, and data-validation testing; validate application behavior against genomics concepts (sequencing data, variant calling, sample traceability); and collaborate with wet lab and dry lab teams to translate laboratory workflows into effective test scenarios.…See more Integrate automated tests into CI/CD pipelines, maintain test data, and partner with engineering and product teams on root-cause analysis and quality issue resolution. Requires 3+ years of QA/test automation experience, strong Python skills, hands-on knowledge of genomics fundamentals, and demonstrated experience testing LIMS platforms and life sciences software.

Bioinformatics QA role focused on designing and executing comprehensive testing, validation, and automation strategies for genomics pipelines and laboratory data platforms. Responsibilities include developing automated test suites in Python, validating NGS workflows (FASTQ, BAM, VCF), performing regression and data-validation testing, and collaborating with wet lab and dry lab teams to ensure scientific and technical correctness.…See more The role requires strong Python scripting, CI/CD pipeline experience, cloud platform familiarity (AWS/GCP/Azure), and working knowledge of genomics science fundamentals including sequencing concepts and LIMS integration.

Design and develop software applications orchestrating complex automated laboratory workflows, closed-loop learning systems, and AI-integrated autonomous discovery ecosystems for biotherapeutics research. Build data pipelines, visualization tools, and machine learning models for visual inspection, predictive maintenance, and process optimization.…See more Create digital lab infrastructure including IoT integrations, digital lab twins, telemetry monitoring, and integrations across automation schedulers, LIMS, and data platforms. Requires Ph.D. in Computer Science/Software Engineering/Bioengineering with 3+ years industry experience (or M.S. with 10+ years, or B.S. with 13+ years), preferably in pharmaceutical or automation sectors.

Build and integrate agentic AI systems with physical laboratory automation platforms (Hamilton, Tecan, Opentrons) and LIMS infrastructure to autonomously design, run, and refine chemistry and biology experiments. Design multi-agent orchestration architectures with state management, error recovery, and tool integration; prototype agent planning strategies and memory systems; deploy containerized services on Kubernetes with GitOps and CI/CD.…See more Work hands-on with chemists, biologists, and automation engineers to transition prototypes into production lab operations that measurably accelerate the Design-Make-Test-Analyze cycle.

Own and evolve the software translation layer between high-level workflow logic and low-level laboratory instrument control, integrating liquid handlers, plate readers, robotic workstations, and analytical instruments. Deploy and maintain containerized services using Docker, Kubernetes, GitOps, and CI/CD practices, building scalable Python applications and data pipelines that connect experimental readouts with LIMS and downstream analysis tools.…See more Collaborate with the team to prototype AI-driven decision-making and autonomous orchestration in lab workflows, evaluating LLM tooling and agent frameworks for practical applicability. Serve as a technical authority and mentor, influencing the broader technical roadmap for autonomous discovery systems and helping grow the automation engineering team's capability.

Design and develop software applications that orchestrate complex automated laboratory workflows and closed-loop learning systems for biotherapeutics discovery. Build data pipelines, visualization tools, and machine learning models for visual inspection, predictive maintenance, and process optimization.…See more Create digital lab infrastructure including IoT integrations, digital lab twins, and telemetry monitoring. Requires a Ph.D. in Computer Science, Software Engineering, or Bioengineering with 3+ years of industry experience, or equivalent education with more experience; strong proficiency in Python, SQL, JavaScript, and DevOps practices; and familiarity with lab data platforms and autonomous systems.

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.…See more 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.