Quantitative Research Engineer

Company Description

At Northwestern Medicine, every patient interaction contributes to fostering a positive working environment. Our patient-centric approach is what differentiates us as a leader in the healthcare sector. Being a part of our team gives you the chance to contribute to our mission of improving healthcare, regardless of your role within the Northwestern Medicine system. Northwestern Medicine prides itself on offering excellent benefits, ranging from tuition reimbursement and loan forgiveness to 401(k) matching and lifecycle benefits, we are committed to taking care of our employees. Ready to join our quest for superior healthcare?

Job Description

The Quantitative Research Engineer embodies the mission, vision, and values of Northwestern Medicine (NM), complies with the organization's Code of Ethics and Corporate Compliance Program, and adheres to all relevant policies, procedures, guidelines, and all other regulatory and accreditation standards.

The Research and Development Engineer is responsible for developing impactful technology. Emphasis is placed on solving real-world issues that are highly compatible with the end user.

Responsibilities:

• Design software and hardware solutions in a collaborative environment.
• Work closely with the end-user to assist and enhance workflows.
• Keep updated on development tools, programming techniques, and computing equipment; engage in educational opportunities; read professional publications.

Qualifications

Required:

• A Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or a related technical field or a Master's degree related to healthcare with some technical background.
• Experience working directly in software development, ML/AI, or a healthcare-related field.
• Exceptional written and verbal communication skills
• Comfortable meeting with both technical and clinical personnel.
• Experience and proficiency with:
  • Handling a wide range of data types (e.g., text, 2D images, time series data)
  • Classic ML techniques (gradient descent, decision trees, etc.)
  • High-level machine learning APIs (Pytorch, JAX, Tensorflow)
  • Design and optimization of data pipelines
  • Python (or similar Object-Oriented language) or C.
  • git/Github
  • Containers

Preferred:

• Advanced degree in Computer Science, Engineering, Mathematics, Physics, or related technical field
• Experience with a variety of data types and manipulations
  • Multimodal unstructured data (text, 2D images, video, 3D/4D tomographic imagery, waveforms, time series, sparse data)
  • A clear understanding of optimized data query writing (SQL, NoSQL, legacy formats)
• ML/AI tools and methods:
  • ML/AI optimization for training (distributed and others) and inference (ONNX)
  • Deep neural network architectures (transformers, convolutional neural networks, recurrent neural networks, etc.)
• Design and optimization of high throughput data pipelines and computer infrastructure
  • Low-level hardware programming (C, C++, Rust, assembly, Verilog/VHDL)
  • Network design and infrastructure
  • Containerization platforms and orchestration infrastructure (Docker, Kubernetes)
  • Hybrid cloud infrastructure combining on-site and off-site high-performance computing.
  • Data and infrastructure security
• Domain-specific tools
  • Weights & Biases/Tensorboard, unit testing methodologies, management of large code bases.
  • Ability to comprehensively document solutions, including diagrams, charts, etc.
  • Integrating the codebase with standardized documentation platforms (Sphinx)
• Healthcare
  • Experience with healthcare data (PHI/HIPAA, HL7 FHIR)
  • Familiarity with FDA regulations
  • Practical clinical 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.