and scale the infrastructure that supports high-performance machine learning and AI-driven research workflows . You will play a critical role in bridging the gap between data science,
bioinformatics, and engineering — ensuring seamless, secure, and reproducible deployment of ML models in production and research environments. You’ll collaborate closely with AI Scientists, Data Engineers, and DevSecOps teams , building automation … and data processing. Build and maintain feature stores, model registries, and versioning systems to ensure traceability and reproducibility. Implement data ingestion and pre-processing pipelines to support ML and
bioinformatics workloads. Collaborate with security and DevSecOps teams to enforce best practices in access control, compliance, and governance . Support AI/ML researchers in model experimentation and infrastructure optimization. Monitor … principles , IAM, and networking best practices. Proficiency in Python and Bash scripting for automation and tooling development. Version control with Git , and collaborative development practices. Desirable Experience Exposure to
bioinformatics or health data ecosystems (WGS, transcriptomics, clinical data). Knowledge of data governance and compliance frameworks (GDPR, ISO27001, HIPAA). Experience building monitoring dashboards for ML performance metrics. Familiarity with
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