Teams at Merge Labs

Build and scale automated research pipelines for molecular engineering, synthetic biology, neuroscience, and brain-computer interface programs. Responsibilities include designing, acquiring, programming, and validating instrumentation and software; integrating metadata, computational design, machine learning, and analysis; building guarded workflow agents; ensuring data quality; and developing custom automation setups with multidisciplinary engineering and research teams.

Build experimental applications and interactive tools for configuring experiments, monitoring execution, visualizing results, and capturing metadata. Integrate instrument APIs with SDKs, data services, backend systems, and automation workflows. Implement testing, logging, failure recovery, CI, packaging, and deployment improvements. Diagnose issues across application, performance, concurrency, native-code, and hardware layers while collaborating directly with scientists and engineers to deliver reliable software.

Design, build, deploy, and maintain critical software supporting scientific experiments, instruments, data systems, and infrastructure. Translate ambiguous research needs into reliable software milestones, develop integrations and high-volume data workflows, solve concurrency and performance issues, and improve testing, observability, and release practices. The role also includes architecture decisions, code review, mentoring, technical leadership, and collaboration with scientists and engineers.