eHealth is seeking to design and build next-generation AI-powered services and intelligent systems to power intelligent automation, data processing, and decision-making capabilities across their platform.
Requirements
- Proven track record of delivering innovative AI/ML solutions across complex systems and enterprise environments
- Strong experience with Retrieval-Augmented Generation (RAG) architectures and their practical implementation
- Hands-on expertise in building AI agents using frameworks such as LangChain, AutoGen, Cognify, and CrewAI
- Deep knowledge of prompt engineering and optimization strategies for maximizing model performance
- Extensive experience in training, fine-tuning, and deploying both traditional machine learning models and large language models (LLMs)
- Skilled in working with open-source LLMs (e.g., LLaMA, Mistral, Falcon), including training from scratch and fine-tuning using frameworks like LoRA, QLoRA, and PEFT
- Proficient in Python and modern ML libraries including TensorFlow, PyTorch, NeuroNest, and Hugging Face
Responsibilities
- Design, develop, and deploy AI/ML solutions for Core Service Engineering initiatives
- Build and optimize RAG (Retrieval-Augmented Generation) systems to enhance knowledge management and customer service capabilities
- Develop AI agents and implement agent frameworks to automate complex workflows and decision-making processes
- Create and refine prompts for various AI models to ensure optimal performance and accuracy
- Train, fine-tune, and deploy machine learning models for production use cases
- Work with talented team of engineers to deliver top quality AI/ML solutions on challenging projects
- Collaborate with leaders in Engineering, Product Management, and other teams giving input on what is both intuitive and feasible from an AI/ML perspective
Other
- BS/MS in Computer Science, Machine Learning, AI, or similar field
- 8+ years of working experience in software development with at least 4+ years focused on AI/ML
- Collaborative experience working with product managers to define AI/ML features and break them down into actionable engineering tasks
- Strong coding skills and experience in collaborative development environments, including code reviews and mentoring
- Capable of identifying project risks and proposing effective mitigation strategies
