CapitalRx
Senior Machine Learning Engineer II
At a Glance
- Location
- Remote
- Work Regime
- remote
- Experience
- 6+ years
- Posted
- 2026-02-12T16:01:19-05:00
Key Requirements
Required Skills
Domain Knowledge
- Engineering
- Legal
- Medical
- Regulatory
Requirements
Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
Minimum 6+ years of experience in industry with a strong focus on ML solutions development and production deployment.
Strong grasp of OOP, Design Patterns, efficient algorithms, and quality software development.
Strong proficiency in Python and familiarity with ML libraries such as PyTorch.
Statistical Machine Learning and Artificial Intelligence in the context of NLP, Speech, RAG, Virtual Agents, and/or Document Processing technologies
Familiarity with cloud platforms such as AWS or Azure.
Responsibilities
Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Senior Machine Learning Engineer. We are looking for an experienced software engineer with machine learning expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services.
In this role you will be expected to design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. The ideal candidate should be passionate about applying AI/ML concepts to difficult problems and develop scalable solutions. We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare.
Design, develop, and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc.
Develop and maintain backend services using Python, focusing on AI-driven applications.
Design and implement APIs for seamless integration with AI models and services.