Machine Learning Operations (MLOps) Engineer
Role details
Job location
Tech stack
Job description
Kforce has a client in Phoenix, AZ that is seeking an experienced MLOps Engineer to join a Data Engineering team and help operationalize machine learning models at scale. Summary: This role sits at the intersection of data engineering, machine learning, and DevOps, with a primary focus on building reliable, automated, and scalable ML pipelines from development through production. The ideal candidate is passionate about turning ML models into production-ready systems, ensuring performance, reliability, monitoring, and governance across the entire ML lifecycle. Key Responsibilities:
- Design, build, and maintain end-to-end ML pipelines that support model training, testing, deployment, and monitoring
- Partner closely with data engineers and data scientists to productionize machine learning models
- Develop and manage CI/CD pipelines for ML workflows, including automated retraining and rollout strategies
- Implement tooling for model versioning, reproducibility, and data validation (e.g., model registries, feature pipelines)
- Monitor model performance in production, identifying drift, degradation, and reliability issues, and implementing corrective actions
- Ensure security, scalability, and data governance standards are met across ML systems
- Contribute to the evolution of the organization's MLOps platform and best practices
Requirements
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience)
- 3-5+ years of experience in MLOps, Data Engineering, DevOps, or ML Engineering roles
- Strong programming experience in Python (experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn preferred)
- Hands-on experience with cloud platforms (AWS, Azure, or GCP)
- Experience with containerization and orchestration tools such as Docker and Kubernetes
- Working knowledge of CI/CD tooling, Git-based workflows, and automation
- Understanding of data pipelines and data engineering concepts
Benefits & conditions
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.
