Data Engineer, Knowledge Graphs
ABOUT MITHRL
We imagine a world where new medicines reach patients in months, not years, and where scientific breakthroughs happen at the speed of thought.
Mithrl is building the world’s first commercially available AI Co-Scientist. It is a discovery engine that transforms messy biological data into insights in minutes. Scientists ask questions in natural language, and Mithrl responds with analysis, novel targets, hypotheses, and patent-ready reports.
Our traction speaks for itself:
12X year-over-year revenue growth
Trusted by leading biotechs and big pharma across three continents
Driving real breakthroughs from target discovery to patient outcomes.
ABOUT THE ROLE
We are hiring a Data Engineer, Knowledge Graphs to build the infrastructure that powers Mithrl’s biological knowledge layer. You will partner closely with the Data Scientist, Knowledge Graphs to take curated knowledge sources and transform them into scalable, reliable, production ready systems that serve the entire platform.
Your work includes building ETL pipelines for large biological datasets, designing schemas and storage models for graph structured data, and creating the API surfaces that allow ML engineers, application teams, and the AI Co-Scientist to query and use the knowledge graph efficiently. You will also own the reliability, performance, and versioning of knowledge graph infrastructure across releases.
This role is the bridge between biological knowledge ingestion and the high performance engineering systems that use it. If you enjoy working on data modeling, schema design, graph storage, ETL, and scalable infrastructure, this is an opportunity to have deep impact on the intelligence layer of Mithrl.
WHAT YOU WILL DO
Build and maintain ETL pipelines for large public biological datasets and curated knowledge sources
Design, implement, and evolve schemas and storage models for graph structured biological data
Create efficient APIs and query surfaces that allow internal teams and AI systems to retrieve nodes, relationships, pathways, annotations, and graph analytics
Partner closely with the Data Scientists to operationalize curated relationships, harmonized variable IDs, metadata standards, and ontology mappings
Build data models that support multi tenant access, versioning, and reproducibility across releases
Implement scalable storage and indexing strategies for high volume graph data
Maintain data quality, validate data integrity, and build monitoring around ingestion and usage
Work with ML engineers and application teams to ensure the knowledge graph infrastructure supports downstream reasoning, analysis, and discovery applications
Support data warehousing, documentation, and API reliability
Ensure performance, reliability, and uptime for knowledge graph services
WHAT YOU BRING
Required Qualifications
Strong experience as a data engineer or backend engineer working with data intensive systems
Experience building ETL or ELT pipelines for large structured or semi structured datasets
Strong understanding of database design, schema modeling, and data architecture
Experience with graph data models or willingness to learn graph storage concepts
Proficiency in Python or similar languages for data engineering
Experience designing and maintaining APIs for data access
Understanding of versioning, provenance, validation, and reproducibility in data systems
Experience with cloud infrastructure and modern data stack tools
Strong communication skills and ability to work closely with scientific and engineering teams
Nice to Have
Experience with graph databases or graph query languages
Experience with biological or chemical data sources
Familiarity with ontologies, controlled vocabularies, and metadata standards
Experience with data warehousing and analytical storage formats
Previous work in a tech bio company or scientific platform environment
WHAT YOU WILL LOVE AT MITHRL
You will build the core infrastructure that makes the biological knowledge graph fast, reliable, and usable
Team: Join a tight-knit, talent-dense team of engineers, scientists, and builders
Culture: We value consistency, clarity, and hard work. We solve hard problems through focused daily execution
Speed: We ship fast (2x/week) and improve continuously based on real user feedback
Location: Beautiful SF office with a high-energy, in-person culture
Benefits: Comprehensive PPO health coverage through Anthem (medical, dental, and vision) + 401(k) with top-tier plans
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.