Senior MLOps Engineer: Deploy & Scale ML Platforms

Fractal Analytics Inc.; New York, Northern (NY, KY); Hybrid; USD 100,000 - 125,000; Full time

Job summary

Fractal Analytics Inc. is seeking a Senior MLOps Engineer (Consultant) in New York to operationalize a portfolio of ML solutions.

You will build production-grade services, data pipelines, and feature engineering frameworks, collaborating with Data Science and Data Engineering teams to deliver scalable inference and ML platform capabilities. The role emphasizes hands-on coding, designing scalable services, and ensuring production-readiness across development, testing, and production environments,

Qualifications

• Deep hands-on Python expertise for data engineering and backend development.
• Strong experience developing production-grade backend services using FastAPI.
• Hands-on expertise with the Databricks platform including MLflow, Delta Lake, Databricks Workflows, and Databricks Asset Bundles (DABs).
• Spark-based distributed processing.
• Proven experience designing end-to-end MLflow-based training and inference architectures across multiple environments.
• Experience with AWS services including SQS, EKS, and Aurora PostgreSQL.
• Experience implementing event-driven and asynchronous architectures using Kafka and/or SQS.
• Strong understanding of the end-to-end ML lifecycle, including feature engineering, training, deployment, monitoring, and retraining.
• Experience creating architecture diagrams, technical design documentation, implementation plans, and operational runbooks.
• Strong Docker and Kubernetes fundamentals.
• Experience with CI/CD pipelines using GitHub Actions, Jenkins, or similar tools.
• Hands-on experience using both GitHub Copilot and Claude Code as part of day-to-day software engineering workflows.
• Excellent written and verbal communication skills with the ability to collaborate effectively with technical and business stakeholders.

Responsibilities

• Design and build FastAPI services exposing models to downstream applications.
• Implement queue-based asynchronous serving patterns using SQS/Kafka for higher latency/throughput workloads.
• Containerize services with Docker and deploy on Kubernetes/EKS with observability and scalability.
• Design end-to-end MLflow-based training and inference architectures across environments.
• Build reproducible ML workflows on Databricks including MLflow, Delta Lake, and DABs.
• Own data preprocessing and feature engineering pipelines for training and inference.

Skills

Python

FastAPI

Databricks

MLflow

Delta Lake

Databricks Workflows

Asset Bundles

Spark

SQS

EKS

Aurora PostgreSQL

Kafka

Docker

Kubernetes

CI/CD

GitHub Actions

Jenkins

GitHub Copilot

Claude Code

Communication skills

Tools

Docker

Kubernetes

Databricks

Job description

Fractal Analytics Inc. is seeking a Senior MLOps Engineer (Consultant) in New York to operationalize a portfolio of ML solutions.

You will build production-grade services, data pipelines, and feature engineering frameworks, collaborating with Data Science and Data Engineering teams to deliver scalable inference and ML platform capabilities. The role emphasizes hands-on coding, designing scalable services, and ensuring production-readiness across development, testing, and production environments,