Machine Learning Engineer developing AI/ML facing applications for Roche's drug discovery process. Collaborating with scientists and engineers to optimize research through AI technologies and methodologies.
Responsibilities
Work closely with Computational Scientists, Research Scientists, AI/ML experts, Product leaders, DevOps, and others
Design, develop, and test robust, scalable, and maintainable AI/ML facing scientific web applications and backend systems
Build tools to evaluate AI/ML model performance and establish new ways to understand AI quality
Partner with product managers and scientists to understand user needs, shape requirements, and translate them into actionable technical specifications
Develop and maintain systems for collecting, structuring, and storing diverse scientific data that support advanced analytics, machine learning, and other data-driven initiatives
Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques
Contribute to architectural decisions, code reviews, and the evolution of our development processes
Stay up-to-date with emerging technologies and industry best practices and adopt a culture of continuous learning, collaboration, and curiosity.
Requirements
Bachelor's or Master’s in Computer Science or similar technical field
2+ years of professional experience in machine learning or similar relevant experience
Strong proficiency with AI/ML frameworks, libraries, and toolsets
Expert knowledge of statistics, machine learning theory, and algorithms
Strong knowledge of ML performance optimization, GPU best practices
Experience with kubernetes, relational databases, NoSQL databases, or data lakes
Experience working on cloud-native architectures in public clouds (ideally AWS)
Proven understanding and application of engineering best practices
Excellent communication skills and ability to build trusted partnerships with internal and external collaborators
Ability to quickly acquire new technologies and programming languages and a passion for continuous learning.
Preferred But Not Required: Experience with imaging or biological data and processes is a strong plus
Experience working with scientists or in a research environment is advantageous
Experience with workflow automation, GenAI, and/or agents is a plus.
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