Senior ML Ops Engineer

About the Company

Confido is the AI infrastructure powering modern CPG — the platform that 200+ brands like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana use to run everything from deductions to production planning. We are a small, in-person team in New York City growing 5x year over year.

Responsibilities

• Own ML pipelines end to end, from experimentation to production, including infrastructure for training, inference, and agentic workloads
• Provide the AI/ML team with reproducible environments and fast paths from prototype to production
• Establish cloud foundation using Infrastructure as Code and CI/CD for safe ML deployment
• Optimize inference and forecasting workloads for latency, throughput, and cost
• Manage the data interface with data engineering to ensure models receive correct data and write outputs back to platform systems
• Implement reliability, observability, security, and privacy as defaults, including online evals and human-in-the-loop review

Requirements

• 5+ years in MLOps, ML platform, AI infrastructure, or platform engineering on production systems
• Proficiency in writing production code and standing up cloud infrastructure
• Experience driving end-to-end pipelines including architecture, security, and cost trade-offs
• Deep understanding of cloud infrastructure, distributed data systems, and IaC
• Strong Python skills and comfort in production app codebases (Ruby, Java)
• High ownership mindset suitable for a fast-moving startup

Preferred Qualifications

• Experience with LLMOps tooling (tracing, prompt/version management, eval harnesses)
• Inference optimization experience (vLLM, ONNX, TensorRT) and GPU economics
• Familiarity with ML orchestration (MLflow, BentoML, Ray, Airflow)
• Experience with large-scale data systems (Snowflake, Kafka) and vector databases
• Knowledge of managed ML services (Bedrock, SageMaker, Vertex AI)
• Experience with multimodal or generative AI in production