Remote MLOps Senior Engineer - Scalable ML Serving

Kforce Inc; Atlanta (GA); Remote; USD 130,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

HSA

FSA

401(k)

Life & disability insurance

Paid time off

Job summary

Kforce Inc is seeking a Remote MLOps Senior Engineer to join a team focused on building and operating scalable ML solutions in a high-volume production environment. You will own production model serving, ML pipelines, and automated workflows on cloud platforms, advancing AI-assisted engineering practices.

The role requires hands-on experience with Python and Java, GCP toolsets, and modern MLOps tooling. You will help drive performance, reliability, and governance for ML systems while

Qualifications

• 5+ years of software engineering experience, with 2–3 years deploying and operating ML models in production.
• Proficiency in Python (FastAPI) and Java (Spring Boot or Micronaut).
• GCP skills: Vertex AI, GKE/Kubernetes, BigQuery, Dataflow.
• Experience with model serving and versioning (Triton Inference Server).
• MLOps practices: CI/CD for models, Airflow, feature stores, monitoring model health and drift.

Responsibilities

• Design, deploy, and support production ML models and model-serving solutions.
• Build and automate training, deployment, and refresh pipelines using workflows and cloud tech.
• Implement monitoring, alerting, testing, and operational controls for ML systems.
• Conduct load testing, performance tuning, and capacity planning for high-traffic services.
• Leverage AI coding assistants and agent-based tools to improve software development and testing workflows.
• Explore LLMs and AI automation to streamline evaluation, monitoring, and deployment validation.

Skills

Python (FastAPI) & Java (Spring Boot/M

Tools

GCP Vertex AI

GKE/Kubernetes

BigQuery

Dataflow

Triton Inference Server

Airflow

CI/CD for ML models

Model monitoring & drift

Job description

Kforce Inc is seeking a Remote MLOps Senior Engineer to join a team focused on building and operating scalable ML solutions in a high-volume production environment. You will own production model serving, ML pipelines, and automated workflows on cloud platforms, advancing AI-assisted engineering practices.

The role requires hands-on experience with Python and Java, GCP toolsets, and modern MLOps tooling. You will help drive performance, reliability, and governance for ML systems while