Job Summary: Please Note: A well-qualified candidate within this department or unit has been identified and will be considered for the position alongside other qualified candidates identified through a competitive recruitment process. The University reserves its right to give priority consideration to internal qualified candidates.
Northwestern University Feinberg School of Medicine (FSM) is dedicated to advancing the development of AI/ML tools and solutions in support of its mission activities. 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 FSM including potential uses in IT, research, education, and operations. research enterprise. The development and deployment of these ML systems will be fully integrated within the Northwestern Medicine Enterprise Data Warehouse (NMEDW) and will be used to establish consistency across the Northwestern Medicine (NM) and Northwestern University environments as well as accelerate AI-driven discovery across the health system.
In this position, you will:
- 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
By actively developing relationships with the research community, the AI/ML Research Scientist will identify and lead the provision of the data science services, resources, and related supports to meet researchers' needs in education, research, IT, and other FSM operational use cases. In partnership with other University groups, the incumbent also fosters the growth, impact, and reach of the data science community at Northwestern.
Specific Responsibilities:
Provide Data Science Support
- Support team and enterprise in developing AI tools and applications
- Train users in ML modeling, architecture and system design, ML Ops and DevOps, and software engineering
- Develop enterprise-scale tools to enable AI research
- Facilitate adoption of existing tools for enabling AI research
Development of ML Models
- Design, train, and evaluate ML/AI models
- Optimize models for performance, scalability, interpretability, and ongoing maintainability
- Apply explainability and fairness techniques to ML models
- Implement uncertainty modeling and clinically meaningful risk thresholds
- Maintain current knowledge of ML and AI advancements
Architecture & System Design
- Design and implement scalable and modular software architectures
- Build and maintain data pipelines for ML workflows
- Design multimodal architectures integrating diverse data modalities (imaging, text, waveforms, structured data, graphs, temporal signals, multi-visit trajectories)
- Balance compliance, performance, and cost in architectural decisions
- Establish and maintain best practices for code quality and documentation
LLM & Generative AI
- Build retrieval-augmented generation (RAG) pipelines and LLM applications
MLops & Production
- Deploy ML models in production environments
- Execute distributed model training on high-performance computing clusters
- Monitor model performance, drift, and operational metrics
- Maintain model versioning and experiment tracking
- Develop dashboards for real-time visualization and ML lifecycle observability
Healthcare & Clinical Research
- Uphold AI governance, compliance, and ethical standards
- Build integrations with Northwestern Medicine Enterprise Data Warehouse
Leadership & Communication
- Lead projects and provide technical direction
- Mentor junior engineers, scientists, or analysts
- Communicate technical findings to stakeholders at various levels
- Collaborate with cross-functional teams to translate requirements into technical solutions
- Foster relationships with researchers and schools/colleges to understand new research trends, identify skill gaps and data science needs, and raise awareness of services
Miscellaneous
Performs other duties as assigned.
Minimum 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.
Minimum Competencies: (Skills, knowledge, and abilities.) Core Programming
- Proficiency in Python, SQL, and/or R.
ML Frameworks & Deep Learning
- 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 & Generative AI
- 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 & Evaluation
- 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 & Infrastructure
- Cloud platform experience (AWS, Azure, or Google Cloud Platform)
- Docker containerization experience
- Kubernetes / container orchestration experience
- CI/CD pipeline experience
- Version control experience (Git)
- Apache Spark / big data tools experience
- ETL/ELT and data warehousing experience
- Unix environment competency
- Terraform and GitHub/Azure DevOps experience
Software Engineering
- 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
Graph & Knowledge Systems
- Hands-on expertise with graph databases and knowledge graph construction
- Experience designing vector search and hybrid vector-graph systems
Healthcare & Clinical Research
- EHR/clinical data integration experience (Epic, FHIR, OMOP)
- Experience in HIPAA-regulated healthcare environments
Leadership & Collaboration
- Strong leadership and communication skills
- Experience leading and mentoring junior engineers or scientists
- Cross-functional collaboration and project management abilities
Preferred Qualifications: - A Bachelor's degree in a related field; a master's degree or PhD is preferred.
Benefits: At Northwestern, we are proud to provide meaningful and competitive benefits. The available benefits package for this position will include 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; and wellness programs. For a comprehensive overview of available benefits, including eligibility details, visit us at to learn more.
Work-Life and Wellness: Northwestern offers comprehensive programs and services to help you and your family navigate life's challenges and opportunities, and adopt and maintain healthy lifestyles.
We support flexible work arrangements where possible and programs to help you locate and pay for quality, affordable childcare and senior/adult care. Visit us at to learn more.
Professional Growth & Development: Northwestern supports employee career development in all circumstances whether your workspace is on campus or at home. If you're interested in developing your professional potential or continuing your formal education, we offer a variety of tools and resources. Visit us at to learn more
. Northwestern University is an Equal Opportunity Employer and does not discriminate on the basis of protected characteristics, including disability and veteran status. View Northwestern's non-discrimination statement . Job applicants who wish to request an accommodation in the application or hiring process should contact the Office of Civil Rights and Title IX Compliance. View additional information on the accommodations process .
Target hiring range for this position will be between $140,250 to $165,000 per year. Offered salary will be determined by the applicant's education, experience, knowledge, skills and abilities, as well as internal equity and alignment with market data.
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