Machine Learning Engineer

Job Title: Sr ML Ops Engineer Location: Davie, FL — Hybrid VISA :- Only US Citizen We are looking for a highly skilled MLOps Engineer to support the end-to-end machine learning lifecycle, from experimentation to production deployment. This role focuses on building scalable, reliable, and automated ML infrastructure, enabling data science teams to deliver production-ready models efficiently and confidently. Key Responsibilities Design, build, and maintain production-grade ML pipelines on Databricks Operationalize ML models, including deployment, monitoring, and lifecycle management Build and maintain CI/CD pipelines for ML workflows Develop and manage real-time and streaming data pipelines Collaborate closely with Data Scientists to productionize models efficiently Implement model versioning, experiment tracking, and reproducibility Define and enforce ML best practices, governance, and quality standards Monitor model performance and data drift; implement automated retraining strategies Optimize performance, scalability, and cost of distributed workloads Contribute to platform design for low-latency inference and scalable serving Required Qualifications (Must-Have) Strong experience with Databricks (Workflows, MLflow, Delta Lake) Deep expertise in Apache Spark (batch and streaming) Advanced Python skills (production-quality code) Hands-on experience with streaming / real-time systems Proven experience designing and implementing CI/CD pipelines Strong understanding of the ML lifecycle (training ? deployment ? monitoring ? retraining) Experience building scalable, distributed data and ML pipelines Nice-to-Have Skills Experience with Snowflake Knowledge of Kubernetes Experience with Docker Familiarity with Terraform or other Infrastructure as Code tools Experience with feature stores (e.g. Snowflake or Databricks Feature Store, etc.) Experience with event-driven architectures (Kafka) Experience with model serving frameworks and low-latency APIs Monitoring and observability tools (ELK or similar) Familiarity with A/B testing / experimentation frameworks Experience with LLM deployment and serving Knowledge of RBAC, security, and governance in data/ML platforms Experience in cloud environments (Azure preferred) #J-18808-Ljbffr BrothersTech