Senior Machine Learning Engineer

Position overview

Responsibilities

• Design, develop, test, deploy, and maintain production ML pipelines and reusable ML services.
• Build evaluation frameworks and automated evaluation pipelines for model quality and performance.
• Develop distributed processing and cloud orchestration for large-scale AI workloads.
• Implement resilient processing, monitoring, observability, drift management, and cost optimization.
• Integrate AI applications with platforms, APIs, identity and access management, and deployment infrastructure.
• Apply MLOps and LLMOps practices, including versioning, tracking, deployment automation, monitoring, rollback, and lifecycle management.
• Translate business problems into ML architectures and communicate designs, behavior, limitations, and trade-offs.
• Support experimentation and prototyping; contribute to engineering standards, architecture, reviews, and documentation.

Minimum qualifications

• Bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, Information Systems, or a related technical discipline.
• 5+ years of machine learning engineering, data engineering, or related experience, including significant production systems experience.
• Demonstrated experience designing and operating production ML systems.
• Strong Python programming skills for production-quality software.
• Working experience with Snowflake utilities, Snow SQL, Snow Pipe, and Snowflake cost optimization.
• Experience with Airflow or comparable workflow orchestration frameworks.
• Experience with data transformation tools such as dbt.
• Hands-on experience building and deploying ML inference pipelines and services.