ML/MLOps Engineer

Sphere; Remote; USD 90,000 - 130,000; Full time

Job summary

A technology organization based in New York is seeking an ML/MLOps Engineer to contribute to production-grade AI systems. The role involves developing and maintaining Python-based services, building ML pipelines, and working with AWS services. Ideal candidates should have experience with Python and MLOps platforms. As part of a fast-paced environment, you'll collaborate with data scientists and product managers to deliver AI-driven solutions. This remote position offers exciting challenges in the AI space.

Qualifications

• Experience with Python (production-quality code).
• Hands-on AWS experience (Lambda, Step Functions, DynamoDB, IAM, containers).
• Experience deploying ML models to production.

Responsibilities

• Develop, maintain, and deploy Python-based production services.
• Build and operate ML pipelines and MLOps infrastructure.
• Deploy, monitor, and maintain ML models in production.

Skills

Python (production-quality code)

AWS (Lambda, Step Functions, DynamoDB)

Kafka or other event-driven systems

MLOps platforms and automation tools

Job description

ML/MLOps Engineer (Python, AWS)

Remotely, Anywhere

We are looking for a ML / MLOps Engineer to contribute to production‑grade AI systems within a fast‑paced technology organization (insurance technology company). The team owns multiple customer‑facing and internal AI applications, including real‑time decisioning, operational automation, chatbots, and ML infrastructure.

Responsibilities

• Develop, maintain, and deploy Python‑based production services
• Build and operate ML pipelines and MLOps infrastructure
• Work with AWS services including Lambda, Step Functions, DynamoDB, Kafka, and containerized applications
• Deploy, monitor, and maintain ML models (e.g., XGBoost) in production environments
• Ensure reliability, correctness, and performance of AI systems
• Ship code to production frequently (daily or near‑daily)
• Debug and resolve production issues efficiently
• Collaborate with data scientists, product managers, and operational teams to support AI‑driven products

Requirements

• Experience with Python (production‑quality code)
• Hands‑on AWS experience (Lambda, Step Functions, DynamoDB, IAM, containers)
• Experience with Kafka or other event‑driven systems
• Experience deploying ML models to production
• Git / CI/CD experience

Nice to Have

• Experience with MLOps platforms and automation tools
• Real‑time data pipelines
• Experience with AI chatbots or retrieval‑augmented generation (RAG) systems