Staff ML Platform Engineer (MLOps) — Remote

FutureFit AI; Toronto; Hybrid; CAD 172,000 - 220,000; Full time

Benefits offered by this job

Remote work

Flexible schedule

Job summary

FutureFit AI is hiring a Staff ML Platform Engineer (MLOps) to own the end-to-end platform beneath our ML and LLM-powered products. You will design and implement compute provisioning, environment management, and cost-aware routing across models, with strong emphasis on observability and traceability.

You will drive experimentation, safe rollout, and production-grade pipelines while staying close to running systems to debug and fix issues quickly.

Qualifications

• Staff-level, hands-on experience in MLOps, ML platform, or ML infrastructure.
• End-to-end CI/CD for models, experiment tracking, registries, and deployment workflows.
• Production experience with LLM-based systems, routing and cost optimization.

Responsibilities

• Own compute provisioning and environment management for reproducible training and serving.
• Build the LLM layer with smart routing and cost-aware model selection.
• Establish deployment and monitoring standards, with traceability and A/B testing.

Skills

MLOps

ML platform

LLM-based systems

CI/CD for models

Data pipelines

Observability

Containerization

Experimentation

Cloud infrastructure

Tools

Airflow

dbt

SageMaker

Python

PostgreSQL

Redshift

MongoDB

Docker

Kubernetes

Job description

FutureFit AI is hiring a Staff ML Platform Engineer (MLOps) to own the end-to-end platform beneath our ML and LLM-powered products. You will design and implement compute provisioning, environment management, and cost-aware routing across models, with strong emphasis on observability and traceability.

You will drive experimentation, safe rollout, and production-grade pipelines while staying close to running systems to debug and fix issues quickly.