Machine Learning PhD Intern

About the role#

Elucid is exploring how large language models and vision-language models can improve patient outcomes and support clinicians. We are looking for a PhD-level intern to join our team in Boston for the winter 2027 term. You will work at the intersection of foundation model research and clinical application, with the potential for your work to influence our current product suite or lead to new publications.

What you'll do#

• Design, build, and evaluate LLM and VLM agents and workflows.
• Create proofs-of-concept for real-world applications of foundation models.
• Partner with engineers, project managers, and clinical staff to develop solutions.

What you'll need#

• Current PhD student in Machine Learning, Computer Science, Electrical Engineering, or a related field.
• Focus on foundation models and an interest in healthcare technology.
• Experience with Python, PyTorch, and tools such as PEFT, LoRA, HuggingFace, or LangGraph for fine-tuning and agentic workflows.
• Experience working with image data and complex, multimodal, or richly labeled datasets.
• Self-driven research background with a history of owning projects from initial idea to final result.
• Ability to communicate clearly and work effectively within a team.
• Preferred: Substantial publications in LLM or VLM domains.
• Preferred: Experience with human-in-the-loop training, RLHF, or tools like nnInteractive.
• Preferred: Experience with AWS services like EC2, S3, or SageMaker.
• Preferred: Experience with biomedical or volumetric data such as DICOMs or cardiovascular imaging.
• Preferred: Experience working in an FDA-regulated environment.

Location & details#

• This is a hybrid role based in Boston, Massachusetts.
• Interns are expected to be in the office at least two days per week, specifically Mondays and Wednesdays.
• This is a paid internship offering $60 to $65 per hour for up to 20 hours per week.
• The term begins in January 2027.