Description
**Position Overview**
The GCF5 Sr Machine Learning Engineer is the senior technical leader for the Agentic & ML Platform pillar. They define and socialize platform standards and patterns, lead multi-team delivery, mentor GCF4 engineers, and translate scientific needs into scalable ML/agentic platform designs. They own pillar-level adoption, reliability, and SLA/SLO outcomes, and influence cross-team engineering quality.
This role reports to the GCF7 leader and partners closely with peer GCF5 domain leads across SCIP to ensure cohesive, scalable platform evolution.
**Core Responsibilities**
+ Own the ML and agentic platform technical roadmap within SCIP.
+ Design and operationalize reusable ML/agentic infrastructure components enabling repeatable deployment.
+ Define evaluation harnesses and model release gates.
+ Establish monitoring, rollback, and observability practices for production ML systems.
+ Implement guardrails and operational controls for safe agentic workflows.
+ Define reproducibility standards and artifact versioning practices.
+ Lead architecture reviews for ML platform evolution.
+ Mentor engineers and elevate ML engineering rigor.
+ Partner with research stakeholders to translate AI use cases into scalable platform capabilities.
**Core Competencies**
+ Deep expertise in the assigned pillar (Agentic & ML Platform) (Agentic‑ML) with evidence of standard‑setting and reuse.
+ Systems design at scale (ML); performance, security, and observability fundamentals.
+ Product/engineering thinking: road mapping, prioritization, and outcome‑oriented delivery.
+ Stakeholder influence across science, engineering, and governance forums; crisp written/verbal communication.
**Core Success Measures**
+ Adoption rate of standardized ML platform components.
+ Evaluation coverage across supported ML use cases.
+ Reduction in model regressions and production ML incidents.
+ Time-to-deploy new ML use cases.
+ Reproducibility rate of experiments and deployments.
+ Reduction in safe-use escalations.
**Key Relationships**
+ Collaborates with GCF6 Group Lead and cross‑functional leaders (R&D/PD/Dev).
+ Mentors and develops GCF4 Data and Software Engineers, partners with platform, data, ML, and research teams.
+ Interfaces with governance (architecture, security, compliance) and vendor/partner teams.
**Decision Authority**
+ Approve designs within the pillar; define and waive standards/patterns with rationale.
+ Recommend buy‑vs‑build; commit pillar resources to meet SLAs/SLOs; escalate risks.
+ Prioritize pillar backlog and roadmap in alignment with strategy and OKRs.
**Qualifications**
Basic Qualifications:
+ BS+8 / MS+6 / PhD in CS/Engineering/Data disciplines.
+ Demonstrated production delivery experience in ML/agentic platforms at scale.
+ Demonstrated literacy in a relevant scientific domain (e.g., biology, chemistry, therapeutic discovery).
Preferred Qualifications:
+ Depth in the assigned pillar (Agentic & ML Platform).
+ Kubernetes and continuous integration/continuous delivery (CI/CD) at scale; observability, performance tuning, and security-by-design.
+ Evidence of standard‑setting and cross‑team influence; mentoring experience.
