Key Responsibilities

- Integrate Foundation Models

Rapidly intake and integrate newly published foundation models (e.g., from academic labs or open-source platforms) into the internal benchmarking system. o Analyze and Troubleshoot Analyze external repositories with incomplete documentation, work backwards from the code to identify required libraries, and successfully resolve environment issues to make the code functional. o Verify Model Integrity

Verify that imported models are working properly and consistently generating expected outputs. across three dimensions data, models, and prediction tasks.

- Execute Data Engineering

Perform data engineering tasks,, and piping datasets into the benchmarking system.

Improve

Infrastructure

Execute infrastructure upgrades, such as for backend databases, data and model processing pipelines, optimizations for speed and robustness
- Support Senior Team Members

Act as a junior maintainer by executing tasks and priorities set by senior team members without needing to independently plan the project roadmap.

Required Qualifications General Skills

Software Engineering

Exceptional software engineering skills with a strong focus on execution and code maintenance. Problem-Solving





Advanced abilities to troubleshoot and operationalize inherited or undocumented code repositories.

- Independent Execution

Proven ability to work independently and execute effectively on directed engineering tasks.

Technical

Skills

- DevOps Capabilities

Strong DevOps skills to assist with model operationalization and infrastructure maintenance.
- Data Pipelining

Solid familiarity with data pipelining and general data engineering tasks.
- Time Zone Availability

Availability to work overlapping hours during morning Eastern Time (ET) for team check-ins and coordination. Preferred Qualifications (Good to Have)
- Machine Learning & AI

Familiarity with building, tuning, and deploying ML/AI models, rather than simply consuming commercially available model endpoints
- Domain Knowledge

Foundational understanding of bioinformatics or biology.
- Bioinformatics Data Engineering

Experience within the bioinformatics scope of data engineering, including curating, joining, and munging biological datasets.Python, git lfs, pytorch / huggingface libraries, sklearn Nice to have CI/CD, containerization, kubeflow, ray pipelines, sksurv, web development (frontend / backend)

📌 Senior Consultant (España)
🏢 Virtusa
📍 España