Machine Learning Engineer with Azure Data Bricks

Role: Machine Learning Engineer with Azure Data Bricks
Location: Seattle, WA
Duration: Long term
Rates: DOE
Note: Core Machine Learning Engineers only (No GenAI and Data Scientist profiles)
Key Responsibilities

• Model Engineering & Deployment: Build and maintain production-grade ML models with an emphasis on real-time inference, scalability, and reliability.
• End-to-End ML Infrastructure: Design and implement scalable ML pipelines on AWS, GCP, or Azure.
• AI/GenAI Strategy: Lead development of advanced LLM and RAG frameworks; drive innovation in ML/GenAI integration strategies.
• Cross-Functional Collaboration: Partner with data scientists, data engineers, DevOps, and business stakeholders to continuously improve AI performance.
• CI/CD Optimization: Develop and maintain CI/CD pipelines for ML using tools such as GitHub Actions.
• Monitoring & Logging: Set up and manage tools to monitor system health and ML model performance.
• Security & Compliance: Ensure ML systems meet telecom and other data privacy regulations.

Required:

• 5+ years of experience as a Machine Learning Engineer.
• Bachelor's degree in Computer Science, Artificial Intelligence, Informatics, or related field.
• Strong knowledge of predictive modeling, NLP, and LLMs, including the use of the RAG framework.
• Hands-on experience with Azure DataBricks.
• Proficiency in Python, SQL, and either R or a comparable language.
• Deep understanding of architecture, containerization (Docker, Kubernetes), and deployment strategies.
• Proven experience building scalable, secure, and compliant AI/ML systems.
• Expertise in CI/CD automation and DevOps collaboration.

Preferred:

• Master's degree in a relevant field.
• Experience working with Telecom systems.
• Certifications in machine learning or cloud computing.