At Copoly.ai, we are a dynamic biotech and AI company driving innovation by working on our own proprietary products and developing specialized solutions for our clients in pharma, biotech, and beyond. We are transforming the future of early cancer detection through AI-powered diagnostic solutions. Our flagship product, OncoSage, leverages RNA sequencing and proprietary class="bg-amber-100">machine learning algorithms to deliver accurate, blood-based cancer detection. We are committed to advancing the field of oncology through cutting-edge technology, improving patient outcomes, and detecting cancer at its earliest stages. Join us in our mission to make revolutionary strides in healthcare technology.

About the Job

We are seeking a highly motivated and skilled Software Engineer (class="bg-amber-100">Frontend class="bg-amber-100">applications) to join our project team at Copoly. This role is dedicated to building intuitive user interfaces and class="bg-amber-100">applications that enable scientists to configure, launch, monitor, and analyze large-scale computational drug discovery workflows to transform drug and target discovery efforts. This work spans large-scale generative models, multi-modal reasoning, and functional therapeutic design, with a strong emphasis on scientific discovery and flexible drug discovery workflows. The successful candidate will work in a multidisciplinary environment alongside AI scientists, AI engineers, and computational and wet-lab biologists to advance the frontier of AI and its impact on healthcare outcomes. 

Key Responsibilities 

• User Interface Development & Deployment: Design and develop user-facing class="bg-amber-100">applications for configuring, launching, and monitoring large-scale computational drug discovery pipelines. 
• Performance & Scientific Insights: Build intuitive visualizations that help scientists monitor computational progress, system performance, and scientific results. 
• System Design: Work directly with researchers to understand their workflows, gather feedback, and rapidly iterate on new features. 
• Software Engineering: Design, implement, test, and maintain production-quality software using modern software engineering best practices. 
• Scientific Collaboration: Participate in class="bg-amber-100">technical discussions, code reviews, and cross-functional planning with ML scientists, engineers, and biologists. 

Educational Background 

• Education: B.S., Master’s or PhD in class="bg-amber-100">Computer Science, Software Engineering, Computational Physical Sciences, or a related quantitative field. 
• Experience: 3+ years of relevant software engineering experience in industry, academia, or other class="bg-amber-100">technical environments 

class="bg-amber-100">Technical Skills 

• Software Engineering: Strong foundations in class="bg-amber-100">data structures, algorithms, and software engineering principles. 
• class="bg-amber-100">Frontend Development: Experience developing modern class="bg-amber-100">web class="bg-amber-100">applications using class="bg-amber-100">frontend frameworks (e.g. class="bg-amber-100">React, TypeScript). 
• class="bg-amber-100">Frontend Integrations: Experience integrating class="bg-amber-100">frontend interfaces with class="bg-amber-100">backend APIs and relational class="bg-amber-100">databases. 
• class="bg-amber-100">Data Visualization: Experience developing dashboards or interactive visualizations for class="bg-amber-100">technical users. 
• Preferred experience: developing class="bg-amber-100">applications for working with or visualizing scientific and engineering class="bg-amber-100">data; “Full-stack” capability working with both class="bg-amber-100">frontend and class="bg-amber-100">backend systems. 

Soft Skills & Professional Attributes 

• Problem Solving: Proven ability to take full ownership of class="bg-amber-100">technical challenges, understand user needs, and proactively drive solutions from start to finish. 
• Communication: Strong class="bg-amber-100">technical communication skills with the ability to articulate complex concepts to both class="bg-amber-100">technical and non-class="bg-amber-100">technical audiences. 
• Domain Knowledge: Prior experience in a drug discovery or a scientific domain such as Chemistry or Biology is strongly preferred but not always required.