Computational Biology MLOps Engineer at Onebridge
San Diego, CA
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Jul 21, 2026
San Diego, CA
Jul 23, 2026
What this job asks for AI summary
This role centers on building and maintaining the ML infrastructure that underpins computational protein design research, sitting at the crossroads of MLOps, high-performance computing, and computational biology. Day-to-day work spans CI/CD pipelines, Kubernetes and SLURM orchestration, and scalable biological data pipelines feeding protein language and generative models. It suits engineers with a solid MLOps background who have an interest in scientific or structural biology data.
Senior level · 5+ years · Indianapolis-Carmel-Anderson, IN
“or” means any one of them counts — you don't need all of them.
Posted 3 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 45 people in the Indianapolis-Carmel-Anderson, IN area plausibly meet what this posting asks for (software developers). range 15–70
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $109,220 (middle half $85,837–$138,030).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (9)
The role is based in Indianapolis, IN or San Diego, CA (CBSA 41740) — two distinct metros. Indianapolis is listed first; San Diego is an equally valid location. The CBSA here reflects Indianapolis only.
The posting requires 5+ years of overall experience and 3+ years of focused MLOps experience; the overall years minimum is set to 5 (the overall floor).
SOC classification is Medium confidence: the role is primarily building and shipping ML infrastructure code (15-1252 Software Developers), but has a strong data pipeline / ETL component that could also point to 15-1243 Database Architects.
GitHub Actions is called out explicitly as a required CI/CD tool, so it is captured as a separate required skill alongside the general CI/CD requirement.
PyTorch is the named primary ML framework; TensorFlow and JAX are listed as alternatives since the JD treats them as interchangeable ('PyTorch, TensorFlow, or JAX').
AWS, GCP, and Azure are listed as interchangeable cloud platforms ('such as AWS, GCP, or Azure'); AWS is the primary with the others as alternatives.
ESM, LangGraph, LangChain, MCP, diffusion models, protein language models, and scientific data formats (PDB/mmCIF) all appear under the 'Preferred' section and are marked accordingly.
LangGraph and MCP are listed alongside LangChain as interchangeable agentic-system options; LangChain is the primary with the others as alternatives.
'Distributed training' is captured as a required skill given the explicit gate on 'distributed training optimization including mixed precision and checkpointing' in the requirements block; it is a methodology/capability rather than a named tool, but the JD treats it as a concrete technical gate here.
Read the full posting
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