Research Engineer, Scientific Data & Workflow Infrastructure
Cambridgeonsitemid$148K – $240K
via Greenhouse
About this role
Your Impact at LILA Lila is building an operating system for science, powered by scientific superintelligence — generating hypotheses, designing and running experiments, and learning from new data in real time to speed up discovery in fields like therapeutics and advanced materials. The Molecular Intelligence team builds ML and physics-based infrastructure for drug discovery: biophysics workflows, computational chemistry tools, cofolding models, low-data learning systems, simulation workflows, and agent-usable scientific pipelines. This role sits embedded with scientists, working closely with Lila’s platform teams on the storage, compute, and orchestration layers beneath it.…
What we'd score you on
reqspace match rubricFive dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.
1
Skills match
For this role: python, kubernetes, airflow, dagster, mlflow…
2
Level fit
This role is mid-level. We check your trajectory against it.
3
Domain experience
Your work in the role's domain matters more than your years total. We weight recent and direct experience.
4
Recency
A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.
5
Location fit
This role is based in Cambridge. We weight your proximity and willingness to relocate.
Score yourself on this role.
Free · no card · written explanation included
Skills in this role
Pulled from the job description. These are the keywords we'll weight when scoring your fit.
pythonkubernetesairflowdagstermlflowrayteams
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