Applied AI Engineer
PhaseV
Applied AI Engineer
PhaseV
SaaS platform for adaptive clinical trials
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, LLMs, and agentic systems alongside proven experience building AI-powered services.
Key Responsibilities
Technical Development:
Research & Analysis:
Collaboration:
Qualifications
Education:
Experience:
Skills:
Preferred:
PhaseVTrials provides a subscription-based software platform that helps pharmaceutical companies, biotech firms, and research teams design, manage, and run adaptive clinical trials. It combines reinforcement learning and causal machine learning to optimize decisions at any stage of a trial, with an intuitive user interface and flexible software architecture that adapts to different clinical needs. Users access the platform via SaaS and can also receive consulting help to fine-tune trial designs and execution strategies. Compared with others, PhaseVTrials offers a distinct mix of advanced data-driven algorithms and a user-friendly tool that delivers real-time insights, aiming to shorten trial timelines and reduce costs. The company’s goal is to accelerate drug development by enabling efficient, data-informed adaptive trials.
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