ML Ops Engineer

Responsibilities Kforce has a client that is seeking a MLOps Engineer in Orlando, FL. Summary: As an MLOps Engineer, you will be responsible for operationalizing machine learning models and ensuring their seamless transition from development to production. You will design, implement, and maintain robust pipelines, infrastructure, and tooling that enable scalable, reliable, and secure AI/ML solutions. Working at the intersection of data science, software engineering, and operations, you will play a vital role in accelerating AI deployment while ensuring models remain effective and maintainable over time. Key Responsibilities: • Design, build, and manage CI/CD pipelines for ML model deployment in cloud and on-premise environments • Containerize and orchestrate ML workloads using Docker and Kubernetes • Integrate models into operational systems via APIs, event-driven workflows, or microservices • Implement model monitoring systems to track performance metrics, data drift, and prediction accuracy • Maintain model versioning and registries to ensure reproducibility and governance • Automate retraining, validation, and redeployment processes to keep models up to date • Work closely with Data Scientist to productionize experimental models • Partner with Data Engineers to design and optimize high-quality data pipelines feeding into ML models • Collaborate with DevOps and IT Security teams to ensure infrastructure compliance, scalability, and security • Optimize computing and storage resource usage for cost efficiency and performance Requirements • Degree in Computer Science, Data Science, Engineering, or equivalent practical experience • Strong programming experience in Python, with knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn) • Hands-on experience with MLOps tools such as MLflow or similar • Experience with DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes) • Knowledge of cloud platforms (Azure, AWS, GCP) for AI/ML services • Understanding of IT security, compliance, and governance for AI systems 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. By clicking “Apply Today” you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.