Senior ML Ops Engineer

Responsibilities

• Own ML pipelines and infrastructure from experimentation through production, including training, inference, and agentic workloads.
• Build reproducible environments and streamlined paths for AI/ML teams to move models and agents from prototypes to production.
• Establish cloud infrastructure as code and CI/CD processes for safe ML deployments.
• Serve and optimize inference and forecasting workloads for latency, throughput, and cost, including asynchronous and parallelized processing.
• Partner with data engineering on model data interfaces and writing model outputs back into platform data systems.
• Make reliability, observability, security, and privacy standard across ML systems.
• Measure model and agent quality in production through online evaluations and human-in-the-loop review.

Requirements

• 5+ years of experience in MLOps, ML platform, AI infrastructure, or platform engineering on production ML systems.
• Strong production software development experience, especially in Python, with comfort working in Ruby or Java codebases.
• Deep understanding of cloud infrastructure, distributed data systems, infrastructure as code, CI/CD, and production containerized workloads.
• Experience owning an end-to-end production ML pipeline and evaluating architecture, security, and cost trade-offs.
• Experience productionizing systems developed by research or AI teams.
• Preferred experience with LLMOps tooling, inference optimization using vLLM, ONNX, or TensorRT, GPU and spot-instance economics, MLflow, BentoML, Ray, Airflow, Snowflake, Kafka, vector databases, Bedrock, SageMaker, Vertex AI, and multimodal or generative AI.

Benefits

• Equity and fully paid employee health coverage through Aetna, plus dental and vision coverage through Guardian.
• Carrot Fertility Pro, 12 weeks of paid parental leave, unlimited PTO, and regular four-day holiday weekends.
• 401(k) through Vestwell.
• Paid relocation support to New York City.
• Fully equipped workspace with a laptop, monitor, keyboard, and a $200 setup stipend.
• Catered Friday lunches, team dinners, unlimited coffee and snacks, and a New York-based work location.