Associate Machine Learning Engineer

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Company Description

At Northwestern Medicine, every patient interaction makes a difference in cultivating a positive workplace. This patient-first approach is what sets us apart as a leader in the healthcare industry. As an integral part of our team, you’ll have the opportunity to join our quest for better healthcare, no matter where you work within the Northwestern Medicine system. At Northwestern Medicine, we pride ourselves on providing competitive benefits: from tuition reimbursement and loan forgiveness to 401(k) matching and lifecycle benefits, we take care of our employees. Ready to join our quest for better?

Job Description

The Associate Machine Learning Engineer, reflects the mission, vision, and values of NM, adheres to the organization’s Code of Ethics and Corporate Compliance Program, and complies with all relevant policies, procedures, guidelines and all other regulatory and accreditation standards.

Northwestern Medicine Information Services drives innovative, high-value solutions to transform health care.   

We are committed to supporting the relentless pursuit of better medicine by providing exceptional service to our patients and guests as well as internal clients across the organization. To ensure excellence, our team goes to extraordinary lengths to ensure that our systems work together seamlessly.  

Northwestern Medicine understands that technology plays an integral role in shaping the future of health care. Information Services strategically supports the organization by:   

  • Leveraging AI, automation and rollout of advanced cyber controls that support digital transformation strategies
  • Implementing advanced technologies in clinical and administrative areas
  • Furthering development of the end user support model to help enhance modern infrastructure

Responsibilities:

  • As a member of the Machine Learning Engineering team, you will work with technical and nontechnical stakeholders to design, build, and manage the infrastructure, platforms, and tools that power AI applications across our health system

Qualifications

Required:

  • Bachelor’s degree or equivalent experience in Computer Science, Engineering, Mathematics, or a related field
  • At least 1 year of experience developing, scaling, or deploying machine learning models
  • Knowledge of machine learning algorithms and principles, and the ability to apply machine learning to real-world problems
  • Professional experience with AWS, Azure, or GCP
  • Proficiency in SQL, Python, and a deep learning framework (e.g. TensorFlow, PyTorch)
  • Hands-on experience with containerization (Docker preferred)
  • Demonstrable experience with version control in a team environment
  • Deep understanding of fundamental computer science concepts, including data structures, algorithms, automated testing, and object-oriented programming
  • A commitment to writing readable, tested, and well-documented code
  • Excellent communication and collaboration skills

Preferred:

  • Master’s or PhD in Computer Science, Engineering, Mathematics, or a related field
  • Production experience with Databricks, Spark, and/or Kubernetes
  • Familiarity with Large Language Models, Generative AI, and RAG systems
  • Knowledge of computer vision workflows and models
  • Familiarity with asynchronous programming patterns
  • Familiarity with GitHub or Azure DevOps
  • Hands-on experience with Terraform
  • Experience with C, C++, C#, or Go
  • Healthcare experience
  • Epic experience

Additional Information

Northwestern Medicine is an affirmative action/equal opportunity employer and does not discriminate in hiring or employment on the basis of age, sex, race, color, religion, national origin, gender identity, veteran status, disability, sexual orientation or any other protected status.

If we offer you a job, we will perform a background check that includes a review of any criminal convictions. A conviction does not disqualify you from employment at Northwestern Medicine. We consider this on a case-by-case basis and follow all state and federal guidelines.

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