Machine Learning Ops Engineer
Core
Architecting and orchestrating multi-cloud infrastructure and automated pipelines to bridge core systems with AI/ML tech stacks for real-time global payments.
Role type
Senior Machine Learning Ops Engineer (MLOps)
Builds
Automated ML pipelines, multi-cloud infrastructure, observability stacks, and cost-optimization controls for LLM and ML systems.
Domain
Fintech / Payments / Machine Learning Operations
Deliverable
production ML models | infrastructure
Required skills
Multi-cloud architecture (AWS/GCP), Infrastructure as Code (Terraform/OpenTofu), DataOps (Medallion Architecture, Airflow), CI/CD automation (GitLab), Containerization (Docker/Kubernetes), LLM observability, Cost optimization, IAM security.
Preferred skills
Experience with self-hosted observability tools (Langfuse, LangSmith, Phoenix), CML (Continuous Machine Learning), dbt, OpenMetadata.
Technologies
Terraform, OpenTofu, Airflow, GitLab, Docker, Kubernetes, AWS, GCP, Redis, Memcached, Langfuse, LangSmith, Phoenix, dbt, OpenMetadata.
Responsibilities
Architect and orchestrate a seamless multi-cloud environment; Design and maintain robust DataOps pipelines implementing Medallion Architecture; Ensure excellence in the MLOps lifecycle (CI, CD, CT, CM); Champion Finance operations for ML and LLM systems; Secure the platform by managing IAM Identity Center; Participate in the evaluation of observability tools.
Seniority
Senior, hands-on IC
