Staff MLOps Engineer
Core
Define and build a unified Enterprise MLOps platform to tie training, deployment, monitoring, and governance together for a regulated financial crime context.
Role type
Staff MLOps Engineer (Platform Architecture & Build)
Builds
Unified MLOps platform layer serving Product Engineering, Intelligence Research, InfoSec, and Operations teams
Domain
Financial Crime / Fintech / Regulated ML Infrastructure
Deliverable
production ML models | infrastructure
Required skills
MLOps platform architecture, build-vs-buy decision making, AWS infrastructure (ECS/EKS, S3, IAM), Databricks ecosystem, model monitoring (drift, bias, evaluation), CI/CD for ML, observability integration, stakeholder management for platform adoption
Preferred skills
Model risk management frameworks, OLAP engines (ClickHouse), Blockchain/crypto domain knowledge, fraud detection modelling, open-source MLOps contributions
Technologies
AWS, Databricks, Terraform, ClickHouse
Responsibilities
Define target-state MLOps architecture and produce decision records, build model training pipelines and serving infrastructure, instrument observability across the ML lifecycle, work with InfoSec to improve model registry and governance, onboard internal consumers onto the platform
Seniority
Staff, hands-on IC with strategic scope
