Machine Learning Operations Engineer I
Core
Build and support a mature ML platform, providing tooling and infrastructure to enable ML engineers to iterate quickly and ship production-ready models, agents, and products.
Role type
MLOps Engineer (IC)
Builds
Internal tooling for ML workflows, model fine-tuning pipelines, RL processes, LLM/Agent evaluation, and observability systems.
Domain
Financial services / Generative AI / MLOps
Deliverable
production ML models
Required skills
Kubernetes, Python, AWS (EKS, Bedrock, SageMaker), distributed computing (Ray), workflow orchestration (Airflow), debugging distributed systems, LLM/Agent concepts
Preferred skills
Agentic AI systems, MCP server patterns, Eval pipelines, open-source tooling adoption
Technologies
Python, Bash, LangGraph, PyTorch, Ray, Amazon EKS, Airflow, Jsonnet, Terraform, Git, AWS, LangFuse, Sentry, Prometheus, W&B
Responsibilities
Develop tools and services to make ML workflows robust and auditable; Evaluate and integrate open-source/third-party solutions; Ship automated processes for model fine-tuning and RL; Improve LLM and Agentic observability; Debug distributed systems across infrastructure and application layers.
Seniority
Junior to Mid-level, hands-on IC
