Applied AI Engineer

Position Overview PhaseV is a technology company that redefines clinical development at scale with its enterprise-ready, multi-modal AI/ML platform. With over $65M raised from top investors, we are poised to make a significant impact on how drugs are developed and brought to market - ultimately helping effective treatments reach patients faster. We are seeking a talented and driven Applied AI Engineer to join our team. This is a unique opportunity to have a direct and real-world impact using AI by helping redefine how clinical trials are designed, optimized, and run. As an Applied AI Engineer, you will also join a high-caliber, multidisciplinary, cross-functional team spanning engineering, data science, and product. This role sits at the intersection of applied AI and product development, with a strong focus on building, deploying, and supporting production-grade AI systems that operate at scale. The ideal candidate will have a strong foundation in NLP and LLMs alongside proven experience building AI-powered services. Key Responsibilities Technical Development: - Build and maintain scalable, production-grade generative AI pipelines that integrate updating unstructured and structured data. - Research and develop robust agentic systems to solve complex clinical problems. - Develop evaluation frameworks for AI systems in clinical contexts. - Optimize representation and retrieval strategies to support explainable outputs. - Contribute to architectural decisions around AI services, APIs, and model orchestration frameworks. Research & Analysis: - Stay up-to-date with the latest developments in AI, machine learning, and related fields, exploring how emerging technologies can be applied to improve products and services. - Document and present methodologies and results for internal and external stakeholders. Collaboration: - Work cross-functionally with engineering, data science, and product teams. - Contribute to technical discussions and peer code reviews. - Support the preparation of technical documentation and research papers. Qualifications Education: - Master's in Computer Science, Data Science, Engineering or a related field - Ph.D. is an advantage but not required Experience: - Strong understanding of NLP, LLMs, entity recognition, and evaluation techniques. - Experience designing and using embedding-based representations, including similarity search and retrieval workflows. - Hands-on experience building agentic workflows in production environments. - Proven experience working with unstructured data (e.g., free text, documents, notes) and applying techniques to transform it into structured formats. Skills: - Strong programming skills in Python. - Ability to clearly communicate complex technical concepts. - Experience with data visualization. - Strong analytical and problem-solving skills. - Ability to work in a dynamic, fast-paced environment. Preferred: - Experience in the healthcare or biotech industry. - Experience with clinical data. - Experience with large-scale data processing.