Senior MLOps Engineer - Build Scalable ML Platforms

Fractal Analytics; New York (NY); On-site; USD 100,000 - 125,000; Full time

Job summary

Fractal Analytics is seeking a Senior MLOps Engineer (Consultant) to operationalize machine learning solutions across purchase and underwriting workflows. You will collaborate with Data Science, Data Engineering, and AI/ML teams to deliver inference services, data pipelines, feature engineering frameworks, and model lifecycle management capabilities.

This hands-on role involves writing production-grade code, designing scalable services, and building reusable ML platform capabilities to ensure

Qualifications

• Deep hands-on Python for data engineering and backend apps.
• Production-grade backend services with FastAPI.

Responsibilities

• Design and build FastAPI services exposing models to downstream apps.
• Implement asynchronous serving using SQS/Kafka.
• Containerize services with Docker and deploy to Kubernetes/EKS.
• MLflow-based training, registry, deployment and inference patterns.
• Build reproducible ML workflows across dev/test/prod.

Skills

Python

FastAPI

Backend development

CI/CD

Distributed systems

GitHub Copilot

Code quality

Tools

Databricks

MLflow

Delta Lake

Docker

Kubernetes

SQS

Kafka

Job description

Fractal Analytics is seeking a Senior MLOps Engineer (Consultant) to operationalize machine learning solutions across purchase and underwriting workflows. You will collaborate with Data Science, Data Engineering, and AI/ML teams to deliver inference services, data pipelines, feature engineering frameworks, and model lifecycle management capabilities.

This hands-on role involves writing production-grade code, designing scalable services, and building reusable ML platform capabilities to ensure