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Senior Engineer, Ontology and Data Standards

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Altos Labs
Contract position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    Data Engineering, Information & Knowledge Management
Salary/Wage Range or Industry Benchmark: 105 - 123 USD Hourly USD 105.00 123.00 HOUR
Job Description & How to Apply Below
Senior Knowledge Engineer, Ontology and Data Standards (Contract)
Our Mission

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.

Diversity at Altos

Altos Labs has been named one of the Top 3 Biotech Companies and ranked for the second year on the Forbes 2026 Best Startups in America list. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives.

We are all accountable for sustaining a diverse and inclusive environment.

What You Will Contribute To Altos
  • As a contract Senior Knowledge Engineer, Ontology and Data Standards, you will drive how our team represents biological knowledge At Altos
  • We have built the machinery: a large canonical LinkML/Biolink schema including REST/MCP/CLI service layer; specification packages covering multiple prior-knowledge sources; and an agentic / human-in-the-loop curation framework. What it lacks is a technical owner—someone to govern and administer the content.
  • You are the scientific translation layer between biological discovery and AI platform engineering. You will elicit implicit models from bench and computational scientists, encode them rigorously, and utilize the agentic workflows that scale curation beyond what manual review can reach.
  • This role carries explicit decision rights: review authority on canonical schema change, ownership of the curation conventions that data atlas and engineering teams follow.

Key Responsibilities

  • Knowledge Modeling & Ontology Engineering:
    • Design, maintain, and extend internal LinkML / Biolink models and ontologies covering experimental and prior-knowledge metadata—driven by competency questions from user requirements and not by source-side convenience.
    • Own mapping and alignment as a discipline: cross-ontology mappings with recorded justification and provenance, and upstream term requests as appropriate.
    • Serve as reviewer of record for schema change, holding the line that reuse precedes coining anything new.
  • Agentic & Automated Curation:
    • Administer, steer, and refine our agentic curation framework and Model Context Protocol (MCP) service layer to scale data profiling, validation, and entity mapping far beyond manual capacity.
    • Standardize tool definitions (FastMCP), prompt templates, and LLM-driven workflows that extract, normalize, and validate metadata from prior-knowledge sources and experimental assets.
  • Biological Data Harmonization:
    • Define mapping patterns and metadata conventions for diverse experimental modalities (genomics, single-cell, screening data) to conform to the canonical schema.
    • Establish standardized conventions that allow both external prior-knowledge sources and internal experimental datasets to cleanly map into the LinkML graph architecture.
  • Quality, Evaluation & Provenance:
    • Establish and maintain automated validation, LLM-assisted quality control, and CI/CD under a "curation as code" paradigm—extending existing drift and coverage gates into the places where semantic review is still manual.
    • Measure whether the knowledge is correct, not merely reproducible: gold-standard sets, inter-curator agreement, and precision/recall on automated extraction.
Who You Are
  • Education & Experience:

    PhD with 5+ years, or MS with 8+ years, in Bioinformatics, Computational Biology, Genomics, Systems Biology, or a related life science field. This is a senior individual-contributor role with organization-wide technical authority and no direct reports.
  • Biological Data Lifecycle:
    Direct experience turning messy, real-world exploratory datasets (genomics,…
Position Requirements
10+ Years work experience
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