MLOps Senior Engineer - Remote

Kforce Inc; Atlanta (GA); Remoto; USD 130.000 - 180.000; Tempo integral

Benefícios oferecidos por esta vaga

Medical insurance

Dental insurance

Vision insurance

HSA

FSA

401(k)

Life & disability insurance

Paid time off

Resumo da vaga

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

Qualificações

• 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.

Responsabilidades

• 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.

Conhecimentos

Python (FastAPI) & Java (Spring Boot/M

Ferramentas

GCP Vertex AI

GKE/Kubernetes

BigQuery

Dataflow

Triton Inference Server

Airflow

CI/CD for ML models

Model monitoring & drift

Descrição da vaga

Responsibilities

Kforce has a client seeking a Remote MLOps Senior Engineer to join their team. The MLOps Senior Engineer will support the development and operation of scalable machine learning solutions in a high-volume production environment. This role will focus on production model serving, ML pipeline automation, system performance, and the adoption of AI-assisted engineering practices. Key Responsibilities:

• Design, deploy, and support production machine learning and model-serving solutions
• Build and automate model training, deployment, and refresh pipelines using workflow orchestration and cloud technologies
• 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, testing, and operational workflows
• Identify opportunities to use LLMs and AI automation to streamline model evaluation, monitoring, deployment validation, and other engineering processes

Responsibilities

Kforce has a client seeking a Remote MLOps Senior Engineer to join their team. The MLOps Senior Engineer will support the development and operation of scalable machine learning solutions in a high-volume production environment. This role will focus on production model serving, ML pipeline automation, system performance, and the adoption of AI-assisted engineering practices. Key Responsibilities:

• Design, deploy, and support production machine learning and model-serving solutions
• Build and automate model training, deployment, and refresh pipelines using workflow orchestration and cloud technologies
• 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, testing, and operational workflows
• Identify opportunities to use LLMs and AI automation to streamline model evaluation, monitoring, deployment validation, and other engineering processes

Requirements

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

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.