Responsibilities

Core (70%)
● CI/CD for models, prompts, and data pipelines
● Model / feature registry with lineage & governance
● Eval harness, canary/rollback, security & secrets
● Full-stack observability (latency, cost, drift)

Support (20%)
● MLOps dashboards
● Performance / cost tuning
● Resilience testing

Cross-team (10%)
● Security reviews
● Change-board
● Incident response

Requirements

● Applied ML/GenAI literacy: review DS code, operationalize models/agents with evals, guardrails, SLOs
● Strong Python: modular, testable code (pytest, black, pylint, CI)
● SWE best practices: Git/GitHub, code reviews, Docker, FastAPI/RESTful services
● At least Upper intermediate level of English

Jobs-To-Be-Done

● Deliver low-latency, SLO-compliant model/agent endpoints
● Enable repeatable CI/CD for models, prompts, pipelines
● Support safe rollouts & instant rollback
● Maintain registry + full observability/reporting
● Ensure reliable data/embedding/indexing pipelines

Impact

● Scale to 5–10 production client models per quarter
● Enable 1–2 new productized releases per quarter
● Boost PoC → production reliability & speed