Senior ML Platform Engineer — Databricks Pipelines

Seminole Hard Rock; United States; On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Benefits package

Job summary

Seminole Hard Rock is seeking a highly skilled MLOps Engineer to support the end-to-end ML lifecycle, from experimentation to production deployment. You will design, build, and maintain production-grade ML pipelines on Databricks and operationalize models with monitoring and retraining capabilities.

The role requires deep Spark expertise, advanced Python, and hands-on experience with streaming systems plus CI/CD for ML workflows.

Qualifications

• 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.

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.

Skills

Databricks

Apache Spark

Python

Streaming systems

CI/CD pipelines

ML lifecycle

Model deployment

Monitoring & observability

Education

Bachelor's degree in Computer Science or related field

Tools

Delta Lake

Kafka

Docker

Kubernetes

Terraform

Snowflake

ELK

Job description

Seminole Hard Rock is seeking a highly skilled MLOps Engineer to support the end-to-end ML lifecycle, from experimentation to production deployment. You will design, build, and maintain production-grade ML pipelines on Databricks and operationalize models with monitoring and retraining capabilities.

The role requires deep Spark expertise, advanced Python, and hands-on experience with streaming systems plus CI/CD for ML workflows.