AI/ML Research Scientist

About the role

The AI/ML Research Scientist leads efforts to develop machine learning for use within a core research infrastructure and prototypes tools, pipelines, and best practices that demonstrate the value of embedded AI/ML support for Northwestern University Feinberg School of Medicine (FSM).

Responsibilities

• Lead and support the development of AI tools and applications for the NMEDW research analytics team and FSM community
• Design, train, and evaluate ML/AI models
• Collaborate with researchers on projects and provide guidance on ML/AI model design and implementation
• Develop enterprise-scale tools to enable AI research
• Deploy ML models in production environments
• Build retrieval-augmented generation (RAG) pipelines and LLM applications
• Mentor junior engineers, scientists, and analysts

Qualifications

• 7 or more years combined work experience and/or post-baccalaureate education in a related field, including experience in informatics, AI, data science, and machine learning.
• Proficiency in Python, SQL, and/or R.
• ML framework experience (TensorFlow, PyTorch, scikit-learn).
• Deep learning expertise (neural networks, NLP, supervised and unsupervised learning).
• Experience fine-tuning deep learning models, including multimodal models.
• Distributed training experience (Ray, DeepSpeed, or FSDP).
• Large-scale data management, processing, and computing cluster experience.
• LLM prompt engineering experience.
• LLM fine-tuning experience (LoRA, PEFT).
• Retrieval-augmented generation (RAG) and vector database experience.
• Experience with LLM solutions and provider APIs (OpenAI, Claude, Anthropic, Azure OpenAI, LangChain).
• Experience with generative modeling or multimodal foundation models.
• Expertise in alignment methods (contrastive learning, RLHF, preference optimization).
• Advanced Architectures:
• Experience building production ML systems with multimodal architectures.
• MLOps platform experience (MLflow, Kubeflow, Airflow).
• Experience defining evaluation frameworks for reasoning and fairness.
• Expertise in explainability or interpretable machine learning.
• Knowledge of monitoring tools for AI model tracking.
• Cloud platform experience (AWS, Azure, or GCP).
• Docker containerization experience.
• Kubernetes / container orchestration experience.
• CI/CD pipeline experience.
• Version control experience (Git).
• Apache Spark / big data tools experience.
• Elasticsearch / big data tools experience.
• Unix environment competency.
• Terraform and GitHub/Azure DevOps experience.
• Software engineering best practices knowledge.
• Strong computer science fundamentals.
• RESTful API and web services experience.
• Frontend development experience (HTML5, CSS3, JavaScript/TypeScript, React or Angular).
• Dashboard deployment experience (Power BI, Dash, Streamlit, React, Flask).
• Open-source ML project contributions.
• Hands-on expertise with graph databases and knowledge graph construction.
• Experience designing vector search and hybrid vector-graph systems.
• EHR/clinical data integration experience (Epic, FHIR, OMOP).
• Experience in HIPAA-regulated healthcare environments.
• Leadership and communication skills.
• Experience leading and mentoring junior engineers or scientists.
• Cross-functional collaboration and project management abilities.

Benefits

• Health, dental, vision, disability, and life insurance
• Paid vacation and holidays
• Paid medical/sick and parental leave
• Tuition benefits for the employee and dependents
• Pre-tax and flex spending accounts for commuting and dependent care
• Generous retirement savings options
• Wellness programs

Pay

$140,250 to $165,000 per year

Schedule

N/A