AI / Machine Learning Summer Intern (Graduate level)

Position Summary: 

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineering Intern.  We are looking for a graduate students with artificial intelligence / machine learning specialization to join us in investigating AI capabilities and tools to improve productivity and create magical experiences in our products and services. 

In this role, you will collaborate with researchers, engineers, and program/project managers to tackle innovative challenges. You will also receive technical mentorship and guidance that allows you to learn new things every day, gain practical skills, build real world experience, develop a greater understanding of the healthcare tech industry, and form valuable connections. Together, you and your team will partner to design and implement an innovative solution for a Machine Learning problem that is meaningful. At the end of your internship, you will have the opportunity to meet and present your work to leadership.  

Responsibilities: 

• Investigate and experiment with tools and methodologies leveraging Artificial Intelligence (AI) and  machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. 

• Work with senior technical staff to develop improvements to models to generate new content using machine learning models in a secure, well-tested, and reasonably performant way. 

• Apply tools and methodologies for large-scale data processing and ETL and contribute to extracting insights from data to help guide ML systems development 

• Ensure the integrity and robustness of ML solutions by executing automated testing and validation processes established within the team. 

• Document and communicate development processes and implementation details with peers and supervisors. 

• Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. 
• Responsible for adherence to the Capital Rx Code of Conduct including reporting of noncompliance.  

Required Qualifications: 

• Working toward a masters or doctoral degree in computer science, engineering, machine learning, applied mathematics, or equivalent. 

• Good understanding or having completed course work of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based LLM and MLMs, Boosted or standard decision trees, RAG, etc.  

• Basic understanding of OOP, Design Patterns, efficient algorithms, and software development lifecycles. 

• Decent proficiency in Python. 

• Good problem-solving skills, attention to detail, and a strong capacity for logical thinking. 

• Some experience crafting, conducting, analyzing, and interpreting experiments and investigations is a plus. 

• Good written communication skills that enable collaboration in a remote and fast-paced environment.