Roche
Overview
Machine Learning Engineer, AI Enablement — Roche. Join to apply for the
Machine Learning Engineer, AI Enablement
role at
Roche . The Position: We advance science so that we all have more time with the people we love. A healthier future. It’s what drives us to innovate and ensure everyone has access to healthcare today and for generations to come. Roche’s AI, data, and computational sciences are transforming drug discovery and development. The new Computational Sciences Center of Excellence (CoE) brings together data and AI to support scientists in both gRED and pRED and accelerate decision-making. The Data and Digital Catalyst (DDC) drives modernization of computational and data ecosystems to enable data-driven science. The Engineering - AI Enablement group within DDC is responsible for enabling AI across our scientific and computational partners, embedding AI into daily work, and building AI-based solutions that scale value and optimize workflows. We work on scaling model training and inference, evaluating AI/ML model quality, and delivering applications that accelerate scientists in drug discovery and development. Our aim is for AI/ML to be an everyday utility across data analysis to literature search and documentation writing. The team is cross-functional, impact-driven, independent, and constantly evolving to meet scientific needs. Responsibilities
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 and data-driven initiatives Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques Contribute to architectural decisions, code reviews, and the evolution of development processes Be willing to span the stack and contribute where needed, even outside of core area of expertise Stay up-to-date with emerging technologies and industry best practices and adopt a culture of continuous learning, collaboration, and curiosity Qualifications
Bachelor's or Master’s in Computer Science or a similar technical field and 2+ years of professional experience in machine learning or related areas Strong proficiency with AI/ML frameworks, libraries, and toolsets Expert knowledge of statistics, machine learning theory, and algorithms Strong knowledge of ML performance optimization and GPU best practices Experience with Kubernetes, relational databases, NoSQL databases, or data lakes, and 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 with a passion for continuous learning Preferred but not required
Experience with imaging or biological data and processes Experience working with scientists or in a research environment Experience with workflow automation, GenAI, and/or agents Additional details
This position requires onsite work 3 days per week. Salary range: $134,100 - $249,100 (based on location: South San Francisco, CA). Actual pay determined by experience, qualifications, location, and other factors. A discretionary annual bonus may be available. Benefits are described in the linked information. Relocation benefits are available. Genentech is an equal opportunity employer. We prohibit unlawful discrimination and ensure merit-based employment decisions in accordance with applicable laws. If you require an accommodation in relation to the online application process, please contact us for accommodations for applicants.
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Machine Learning Engineer, AI Enablement — Roche. Join to apply for the
Machine Learning Engineer, AI Enablement
role at
Roche . The Position: We advance science so that we all have more time with the people we love. A healthier future. It’s what drives us to innovate and ensure everyone has access to healthcare today and for generations to come. Roche’s AI, data, and computational sciences are transforming drug discovery and development. The new Computational Sciences Center of Excellence (CoE) brings together data and AI to support scientists in both gRED and pRED and accelerate decision-making. The Data and Digital Catalyst (DDC) drives modernization of computational and data ecosystems to enable data-driven science. The Engineering - AI Enablement group within DDC is responsible for enabling AI across our scientific and computational partners, embedding AI into daily work, and building AI-based solutions that scale value and optimize workflows. We work on scaling model training and inference, evaluating AI/ML model quality, and delivering applications that accelerate scientists in drug discovery and development. Our aim is for AI/ML to be an everyday utility across data analysis to literature search and documentation writing. The team is cross-functional, impact-driven, independent, and constantly evolving to meet scientific needs. Responsibilities
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 and data-driven initiatives Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques Contribute to architectural decisions, code reviews, and the evolution of development processes Be willing to span the stack and contribute where needed, even outside of core area of expertise Stay up-to-date with emerging technologies and industry best practices and adopt a culture of continuous learning, collaboration, and curiosity Qualifications
Bachelor's or Master’s in Computer Science or a similar technical field and 2+ years of professional experience in machine learning or related areas Strong proficiency with AI/ML frameworks, libraries, and toolsets Expert knowledge of statistics, machine learning theory, and algorithms Strong knowledge of ML performance optimization and GPU best practices Experience with Kubernetes, relational databases, NoSQL databases, or data lakes, and 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 with a passion for continuous learning Preferred but not required
Experience with imaging or biological data and processes Experience working with scientists or in a research environment Experience with workflow automation, GenAI, and/or agents Additional details
This position requires onsite work 3 days per week. Salary range: $134,100 - $249,100 (based on location: South San Francisco, CA). Actual pay determined by experience, qualifications, location, and other factors. A discretionary annual bonus may be available. Benefits are described in the linked information. Relocation benefits are available. Genentech is an equal opportunity employer. We prohibit unlawful discrimination and ensure merit-based employment decisions in accordance with applicable laws. If you require an accommodation in relation to the online application process, please contact us for accommodations for applicants.
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