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LeadFull-timePythonRustCI/CDAIML
Salary Range
$140,250 - $189,750 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Forward Deployed Scientist to join Prima Mente, a frontier biology AI lab. This role involves embedding our flagship model Pleiades with early partners to test research outcomes and product hypotheses, and leading the build out of our FDS model.
Key Responsibilities
- →Design, lead and own our Forward Deployment function
- →Directly manage our end-to-end customer implementation strategy and execution
- →Embed with early design partners to deeply understand their use-cases for cfDNA fragment analysis, epigenetic embedding, multi-omic integration, diagnostic reporting, patient-specific risk stratification
- →Translate real-world problems into concrete, deployable solutions, including designing and building custom pipelines, data ingestion, model integration, and output handling
- →Act as the primary technical owner, building trust and guiding the customer's own teams
- →Establish deployment best practices and find reusable patterns
- →Feed what you learn from deployments back into the R&D roadmap to help prioritize model improvements, new features, and research directions
Requirements
- ✓Deep customer fluency and empathy, able to explain complex systems to non-technical executives and understand their business problems
- ✓Strong programming and scripting skills (Python or equivalent), able to build bioinformatics pipelines and integrate ML models into production environments
- ✓Experience building tools or frameworks for ML/AI workloads, including data pipelines, infrastructure, modular/reusable code, CI/CD for ML, and monitoring
- ✓Bias for moving fast, iteration, and scope adjustment to the most useful thing possible given constraints
- ✓Comfort with ambiguity and early-stage work, able to navigate messy, incomplete data, iterate quickly, improvise tools, and own the entire deployment stack end-to-end
- ✓Prior experience deploying ML/AI in regulated or high-stakes environments (clinical labs, healthcare, diagnostics, enterprise)
- ✓Familiarity with compliance and data governance (e.g., data anonymization, GDPR, audit-ability, provenance)
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