Senior Data Scientist - Production ML & MLOps on Databricks

Recru; Spring (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Recru in Spring, TX is seeking a Senior Data Scientist to design, build and deploy production-grade ML solutions on the Databricks AI Platform. You will champion scalable, enterprise-grade ML with a strong focus on MLOps and CI/CD.

Leverage feature engineering, model serving, and lakehouse architecture while collaborating with cross-functional teams to ensure reliability in production environments.

Qualifications

• 8+ years of hands-on experience building, deploying, and supporting ML solutions in production.
• Deep expertise with the Databricks AI Platform, including MLflow, Unity Catalog, Feature Engineering, Model Serving, Lakehouse Architecture, and end-to-end MLOps.
• Strong software engineering background with Git, CI/CD pipelines, automated testing, deployment automation, monitoring, and observability.
• Experience with Azure DevOps or comparable DevOps platforms.
• Proven ability to support and optimize AI/ML solutions in enterprise production environments.

Responsibilities

• Design and architect production-grade machine learning solutions.
• Build and deploy scalable AI/ML models on the Databricks AI Platform.
• Implement MLOps best practices, including CI/CD pipelines and automated testing.
• Integrate feature engineering, model serving, and lakehouse architecture.
• Monitor, troubleshoot, and optimize AI/ML solutions in enterprise production environments.
• Collaborate with cross-functional teams to ensure reliability and scalability.

Skills

MLOps

Databricks ML Platform

MLflow

Feature Engineering

Model Serving

Lakehouse Architecture

CI/CD pipelines

Observability

Azure DevOps

Git

Tools

Git

CI/CD

Job description

Recru in Spring, TX is seeking a Senior Data Scientist to design, build and deploy production-grade ML solutions on the Databricks AI Platform. You will champion scalable, enterprise-grade ML with a strong focus on MLOps and CI/CD.

Leverage feature engineering, model serving, and lakehouse architecture while collaborating with cross-functional teams to ensure reliability in production environments.