AI/ML Research Scientist

Job Summary:

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 GCP)

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 https://www.northwestern.edu/hr/benefits/index.html 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 https://www.northwestern.edu/hr/benefits/work-life/index.html 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 https://www.northwestern.edu/hr/learning/index.html 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.

#LI-MB1

• 7+ years experience and/or post-baccalaureate education in informatics, AI, data science, and machine learning
• Proficiency in Python, SQL, and/or R; experience with ML frameworks (TensorFlow, PyTorch) and deep learning
• Expertise in deploying production ML systems, cloud platforms (AWS, Azure, GCP), MLOps, and leadership skills