Machine Learning Engineer

We’re partnering with an innovative organization in the south metro of the Twin Cities seeking a Machine Learning Engineer to help advance and scale their machine learning capabilities within a Snowflake-driven data ecosystem.

This is a high-impact role for someone who thrives at the intersection of architecture, production ML, and MLOps strategy. You’ll play a key role in shaping how models move from experimentation to secure, scalable, enterprise-grade solutions.

Key Responsibilities

• Lead the design, engineering, and productionization of machine learning solutions.
• Architect scalable ML pipelines leveraging Snowflake as the core data foundation.
• Partner closely with data scientists to operationalize models with rigor, reliability, and long-term supportability.
• Strengthen and mature MLOps practices, CI/CD pipelines, monitoring frameworks, and model governance.
• Optimize model performance, scalability, and cost efficiency across cloud-based ML environments.
• Provide senior-level technical leadership and influence platform decisions.
• Ensure security, compliance, and data governance best practices are embedded in ML workflows.
• Identify opportunities to modernize tooling and improve ML lifecycle management.
• Contribute to a collaborative, cross-functional engineering culture.

Required Experience

Technical

• 6+ years of experience in machine learning engineering, data engineering, or related roles.
• Advanced proficiency in SQL (Snowflake experience strongly preferred).
• Experience building and scaling ML pipelines in cloud-based ecosystems.
• Experience working within Snowflake data environments.
• Azure ML or other ML platform experience a plus.
• Deep understanding of CI/CD, version control (Git), and production deployment best practices.
• Experience with model monitoring, retraining strategies, and ML lifecycle management.

Professional

• Proven ability to influence technical direction and architecture decisions.
• Strong systems-thinking mindset.
• Excellent communication skills — able to bridge data science and engineering teams.
• High ownership mentality with a proactive approach.
• Collaborative leader who elevates the broader team.