Clinical AI Engineering Intern

Your Future is our Future

At Lumeris, we believe that our greatest achievements are made possible by the talent and commitment of our team members. That's why we are actively seeking talented and collaborative individuals who are passionate about making a difference in the healthcare industry. Join us today as we strive to create a system of care that every doctor wants for their own family and become part of a community that values its people and empowers you to make an impact.

Position:

Clinical AI Engineering Intern

Position Summary:

Lumeris is physician-founded, mission-driven, and building the future of primary care. Our platform, Tom, is an agentic AI that works alongside care teams - automating routine tasks, surfacing the Best Next Action for every patient in real time, and delivering proactive outreach before, during, and after patient visits. Built on billions of clinical data points and over 100 EHR integrations, Tom powers Primary Care as a Service - helping health systems improve outcomes, reduce burden on physicians, and deliver value-based care at scale.

As an AI/ML Intern at Lumeris, you will work directly on the technical core of Tom - building and fine-tuning large language models using real-world longitudinal clinical data. The goal: expand Tom's predictive capabilities, with specific targets including 30-day readmission rates and time-to-event modeling. This is not a passive learning experience. You will be an active contributor to a defined, high-impact research initiative running on Google Cloud Platform, working alongside ML engineers, data scientists, and clinical informatics experts. The work is experimental, scientifically rigorous, and directly tied to patient outcomes.

• Applicants must be based in the greater Boston area with ability to travel to Cambridge 3-days per week.

Job Description:

Primary Responsibilities

• LLM Training & Model Development

• Fine-tune and train large language models using longitudinal clinical patient data on GCP infrastructure, with a focus on expanding Tom's predictive capabilities.

• Contribute to the design and experimentation of transformer-based architectures and embedding models aimed at predicting specific clinical outcomes.

• Assist in evaluating model performance against defined prediction targets including 30-day readmissions and time-to-event events.

• Experimentation & Research

• Operate in an experiment-driven development environment - designing tests, iterating on model behavior, tracking results, and documenting findings with scientific rigor.

• Explore and apply LLM fine-tuning techniques (e.g., LoRA, PEFT, supervised fine-tuning) appropriate to the clinical data and prediction objectives.

• Contribute to the team's working knowledge of embedding models, sequence-based architectures, and clinical data preprocessing.

• Collaboration & Deliverables

• Work cross-functionally with ML engineers, clinical informatics specialists, and data scientists in a highly collaborative research environment.

• Engage with a structured mentorship model - supported by project mentors and a dedicated technical mentor throughout the engagement.

• Prepare and present a formal project deliverable at the conclusion of the internship, summarizing methodology, outcomes, and recommendations.

Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Computational Biology, Biomedical Informatics, or a closely related field.

• Coursework or hands-on experience in machine learning, deep learning, or neural networks.

• Foundational understanding of how LLMs work, including transformer architectures and model training pipelines.

• Strong analytical and problem-solving skills with a scientific, experiment-driven mindset.

• Effective communication skills and ability to work collaboratively in a research-oriented team environment.

Preferred

• Experience with LLM fine-tuning techniques (e.g., LoRA, PEFT, instruction tuning, supervised fine-tuning).

• Familiarity with Google Cloud Platform (GCP) or other cloud environments for ML workloads.

• Experience with Survival Modeling Techniques

• Experience with standard medical terminologies like OMOP, FHIR

• Background in clinical informatics, bioinformatics, or healthcare data.

• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers.

• Prior research experience (academic, industry, or self-directed) - particularly in applied ML or healthcare AI.

• Exposure to embedding models, vector databases, or sequence-based modeling.

• Graduate-level coursework in NLP, deep learning, or biomedical data science is a strong plus.

Pay Transparency:

Factors that may be used to determine your actual pay rate include your specific skills, experience, qualifications, location, and comparison to other employees already in this role. In addition to the base salary, certain roles may qualify for a performance-based incentive and/or equity, with eligibility depending on the position. These rewards are based on a combination of company performance and individual achievements.

The hiring range for this position is:

$54,800.00-$73,250.00

Benefits of working at Lumeris

• Medical, Vision and Dental Plans

• Tax-Advantage Savings Accounts (FSA & HSA)

• Life Insurance and Disability Insurance

• Paid Time Off (PTO, Sick Time, Paid Leave, Volunteer & Wellness Days)

• Employee Assistance Program

• 401k with company match

• Employee Resource Groups

• Employee Discount Program

• Learning and Development Opportunities

• And much more...

Be part of a team that is changing healthcare!

Member Facing Position:

No- Not Member or Patient Facing Position

Location:

Massachusetts

Time Type:

Full time

Lumeris and its partners are committed to protecting our high-risk members & prospects when conducting business in-person. All personnel who interact with at-risk members or prospects are required to have completed, at a minimum, the initial series of an approved COVID-19 vaccine. If this role has been identified as member-facing, proof of vaccination will be required as a condition of employment.

Disclaimer:

• The job description describes the general nature and level of work being performed by people assigned to this job and is not intended to be an exhaustive list of all responsibilities, duties and skills required. The physical activities, demands and working conditions represent those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individual with disabilities to perform the essential job duties and responsibilities.

Lumeris is an EEO/AA employer M/F/V/D.