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.