Scientific Data Engineer
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Key skills for this role
Role Overview
The Scientific Data Engineer will build software, data, and analytical systems supporting scientific workflows.
The initial focus is image analysis, with additional work on ultrasound data, data modeling, and analysis across experimental modalities.
The role owns workflows from raw experimental inputs through validated, reproducible results.
Key Skills for This Role
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About Merge Labs
Merge Labs is a frontier research lab developing brain-computer interfaces that connect biological systems and artificial intelligence.
The lab focuses on high-bandwidth brain interaction, advanced AI integration, safety, accessibility, and human agency.
About the Team
The Software & Data Engineering team builds computational foundations for turning complex experimental data into reliable scientific insight.
The team develops reusable analysis libraries, data models, workflow infrastructure, and tools for exploring scientific results.
About the Role
The Scientific Data Engineer will build software, data, and analytical systems supporting scientific workflows.
The initial focus is image analysis, with additional work on ultrasound data, data modeling, and analysis across experimental modalities.
The role owns workflows from raw experimental inputs through validated, reproducible results.
Responsibilities
- Design and maintain reusable Python libraries for scientific and image analysis and quality control.
- Build reproducible analysis pipelines integrated with workflow-management and scientific data systems.
- Define data models for raw data, metadata, derived results, and analysis provenance.
- Partner with wet-lab and computational scientists to develop validated, maintainable solutions.
- Establish testing, validation, versioning, observability, and failure-handling practices.
- Evaluate external tools, make build-versus-buy decisions, and define adaptable system interfaces.
- Balance immediate experimental needs with investments in shared research infrastructure.
Qualifications
- Strong Python software engineering experience including API design, testing, packaging, code review, and Git collaboration.
- Experience designing scientific image-analysis pipelines and validating classical or learned methods.
- Experience with quantitative validation, quality control, reproducibility, provenance, and failure-mode handling.
- Experience with workflow orchestration systems such as Dagster, Prefect, or Airflow.
- Experience collaborating directly with wet-lab scientists on ambiguous scientific needs.
- Ability to make thoughtful trade-offs among speed, maintainability, reliability, performance, and cost.
- Ownership and judgment to independently drive important projects to completion.
Helpful Experience
- Experience with Bazel or another large monorepo build system is helpful but not required.
- Experience with next-generation sequencing, spatial omics, ultrasound, or other scientific modalities is helpful but not required.
- Experience in an early-stage or rapidly changing research environment is helpful but not required.
About merge labs
Private brain-computer interface research laboratory developing high-bandwidth, AI-integrated technologies for patients and broader human capability.
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