Job Summary
Regenstrief Center for Healthcare Engineering conducts research to improve the quality, accessibility, and affordability of healthcare delivery through collaboration, partnerships, and engagement.
To fulfill our mission, we:
- Improve healthcare delivery and patient outcomes through the deployment of sustainable solutions.
- At Purdue, we believe in practical and applied impact—our research doesn’t just stay in the lab; it shapes real-world healthcare outcomes. By leveraging interdisciplinary strengths and a culture of resilience, we develop sustainable solutions that make a tangible difference for patients and communities.
- Harness the power of health and healthcare data via our strengths in computer science, statistics, and mathematics, to improve patients' experiences, outcomes, and population health.
- Purdue’s legacy of excellence in data-driven research is foundational to our work at RCHE. By uniting expertise across disciplines, we unlock new insights from healthcare data, driving advancements that improve the experiences and health of individuals and populations.
- Break down communication boundaries to translate innovative solutions that can improve everyone’s health and wellbeing.
- We foster an environment where collaboration transcends boundaries. Purdue’s culture is built on respect, shared experiences, and a commitment to working together—qualities that enable us to deliver innovations that benefit all.
The Lead Data Scientist will be a key member of our data science and engineering team, leading the development of secure, scalable, and innovative data solutions to support research, education, and outreach initiatives. This senior-level role requires deep expertise in machine learning—especially large language models (LLMs)—and their surrounding infrastructure, tooling, and deployment pipelines.
The Lead Data Scientist will advise and guide the team on the integration and responsible use of LLMs and related generative AI technologies. They will design and implement advanced ML workflows, including model selection, fine tuning, prompt engineering, evaluation, and deployment. The ideal candidate will bring significant experience with the architecture of LLM systems, including tokenization, transformer layers, vector databases, model inference, fine-tuning strategies (e.g., LoRA, PEFT), and RLHF (Reinforcement Learning with Human Feedback). This position also supports national computing initiatives through workshops, conferences, publications, and proposal development.
At Purdue, you’ll join a community where unrivaled pride and unlimited potential are more than just words—they’re the foundation of how we work and grow, together. If you’re ready to help build a better world through research that matters, take the next step and join us on this path.
This is a hybrid position.
About Us:
When you join Purdue University, you join a community that keeps moving forward. For more than 150 years, we’ve been known for not only our groundbreaking work in STEM research, but also for our collective imagination, ingenuity and innovation.
What We're Looking For:
Education and Experience
Qualified candidates will need:
- Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
- Five or more years of experience in machine learning, deep learning, or AI systems development.
- Demonstrated experience working with transformer-based models and LLM ecosystems.
- Experience designing and deploying production-grade AI/ML solutions, including prompt engineering, fine-tuning, and inference pipelines.
Skills:
- Deep knowledge of machine learning architecture, including attention mechanisms, tokenization, embedding layers, and vector search.
- Proficient in Python and ML frameworks (e.g., PyTorch, Tensor Flow, Hugging Face).
- Experience building and deploying LLM-based applications with cloud platforms (e.g., Azure, AWS, Google Cloud).
- Strong communication and mentoring skills, with the ability to translate complex AI concepts into actionable strategies.
Nice to have:
- Ph.D. Degree in Computer Science, Computer Engineering, Computer Information Technology, Statistics, or a related field
- Experience with LLMOps and MLOps tools such as MLflow, Weights & Biases, LangChain, or Hugging Face Hub.
- Familiarity with healthcare data and ethical considerations in generative AI applications.
- Contributions to open-source LLM projects or publications in AI/ML venues.
Additional Information:
- Purdue will not sponsor employment authorization for this position
- A background check will be required for employment in this position
- FLSA: Exempt (Not Eligible For Overtime)
- Retirement Eligibility: Defined Contributions immediately
- Purdue University is an EOE/AA employer.
Who We Are:
Purdue is a community built on collaboration, with global perspectives, Boilermaker pride and endless opportunity to live, learn and grow. Join us and contribute to our culture.
Career Stream
Compensation Information:
Professional 4
Pay Band S085
Job Code # 20003055