Machine Learning Engineer

About this role

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Skills you'll use

What you'll do

• 3M Health Care is now Solventum
• At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers’ toughest challenges, we pioneer game-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue.
• We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you.
• The Impact You’ll Make in this Role
• As an ML Engineer, you will be responsible for building and maintaining the pipelines that power AI in our Healthcare Information Systems (HIS). We are looking for a practical, detail-oriented engineer who is passionate about MLOps, data reliability, and production stability.
• In this role, you won’t just be building models; you will be ensuring those models work reliably in the real world. You will help bridge the gap between data science and software engineering by implementing automated workflows, managing cloud infrastructure, and ensuring our AI services are secure and scalable.

Who can apply

• To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications:
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• 3–5 years of professional experience in software engineering or data engineering, with at least 2 years focused on machine learning production environments.
• Programming: Strong proficiency in Python and familiarity with SQL. Knowledge of a compiled language (like Go or Java) is a plus.
• Cloud & Infrastructure: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and containerization (Docker).
• ML Tools: Familiarity with ML libraries (PyTorch or Scikit-learn) and MLOps tools (like Airflow, Prefect, BentoML, or Kubeflow).
• Data Tools: Experience with data processing frameworks (like Pandas, Spark, or dbt).

About Solventum

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