Senior MLOps Engineer

DescriptionKforce has a client seeking a Senior MLOps Engineer in Fort Lauderdale, FL to join a high-performing team focused on building and scaling enterprise machine learning platforms. This role is responsible for designing, deploying, and optimizing production-grade ML infrastructure that enables data science teams to efficiently move models from experimentation to production.The ideal candidate has deep experience with Databricks, Apache Spark, Python, and CI/CD practices, along with a strong understanding of the full machine learning lifecycle. This position offers the opportunity to support innovative initiatives involving real-time analytics, recommendation engines, customer personalization, and AI-powered applications.Responsibilities:* Design, build, and maintain scalable machine learning pipelines on Databricks* Deploy, monitor, and manage machine learning models in production environments* Develop and maintain CI/CD pipelines for ML and data workflows* Build and support batch, streaming, and real-time data pipelines* Partner with Data Scientists to operationalize and optimize machine learning solutions* Implement model versioning, experiment tracking, and reproducible ML processes* Establish and promote ML engineering best practices, governance, and quality standards* Monitor model performance, data quality, and drift while supporting automated retraining strategies* Optimize distributed workloads for performance, scalability, and cost efficiency* Contribute to platform architecture supporting low-latency model inference and scalable model servingRequirements* Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience* Strong experience with Databricks, including Workflows, MLflow, and Delta Lake* Advanced expertise with Apache Spark for batch and streaming data processing* Strong Python development skills with experience building production-quality applications* Experience designing and implementing CI/CD pipelines for data and machine learning workloads* Knowledge of machine learning lifecycle management, including training, deployment, monitoring, and retraining* Experience building scalable and distributed data pipelines and ML systems* Hands-on experience with real-time or streaming architectures* Experience working in Azure cloud environmentsPreferred Skills:* Snowflake* Kubernetes* Docker* Terraform or other Infrastructure-as-Code tools* Feature Store technologies* Kafka or event-driven architectures* Model serving frameworks and low-latency API development* ELK Stack or similar monitoring and observability platforms* A/B testing and experimentation frameworks* Large Language Model (LLM) deployment and serving* RBAC, security, and governance within data and ML platformsJob TypeContractCompensation89 - $120