Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) need to leverage advances in AI, data, and computational sciences to accelerate drug discovery and development. Seamless data sharing and access to models across gRED and pRED are essential to maximizing these opportunities. The new Computational Sciences Center of Excellence (CoE) aims to harness the transformative power of data and Artificial Intelligence (AI) to assist scientists in delivering more innovative and transformative medicines.
Requirements
- 2+ years of industry experience in machine learning; or a PhD in Computer Science and related field and 0+ years of industry experience.
- Demonstrated success in technical capabilities deploying machine learning models in industry-grade production environments
- Experience in back-end development for LLM-powered agents and tools, or working with Model Context Protocol (MCP).
- Experience in developing LLM/GenAI products and are familiar with open-source AI frameworks like Open WebUI.
- Strong programming skills in Python and using deep learning frameworks like PyTorch
- Extensive experience with deep learning & LLMs.
Responsibilities
- Develop various, cutting-edge AI/ML-based applications for drug discovery and development.
- Develop across the lifecycle of LLMs including data engineering, pre-training, fine-tuning, post-training, and evaluation
- Deploy models in production environments, working closely with other engineers to ensure scalability and reliability
- Solve core backend challenges in ML and engineering including the design, implementation, and scaling of our data, training, and deployment pipeline
- Collaborate closely with cross-functional teams across both AIDD and Roche to solve complex problems in the life sciences
Other
- The ideal candidate should have extensive experience in leading and managing a team of engineers and scientists, and be able to foster a culture of innovation, collaboration, and excellence across the broader Roche organization.
- A collaborative and open-minded team player who values constructive feedback, refrains from judgment, and fosters a positive and respectful team environment.
- Strong communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific and engineering leadership
- A passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning
- An extensive track record of delivering innovative solutions in machine learning
