Machine Learning Engineer/Senior Machine Learning...

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide., At Roche’s AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. We are seeking a highly motivated and skilled ML Engineer to join our growing team within Genentech Research and Early Development AI Drug Development (gRED AIDD). This role is crucial for enhancing the core features that power our machine learning initiatives. The ideal candidate will have deep experience building scalable software and infrastructure, while consistently adhering to corporate standards and best practices.

What you’ll do

Machine Learning Engineer - Infra

• Design, implement, and maintain scalable and reliable ML infrastructure

• Collaborate closely with ML engineers and data scientists to understand and address their infrastructure needs.

• Document infrastructure designs, processes, and operational procedures.

Senior Machine Learning Engineer - Infra

• Design, implement, and maintain scalable and reliable ML infrastructure, leading the architecture and delivery of significant technical solutions.

• Proactively identify and solve complex, often cross-functional, technical problems within the ML infrastructure domain.

• Collaborate closely with ML engineers and data scientists to understand and address their infrastructure needs.

• Document infrastructure designs, processes, and operational procedures.

• Mentor junior engineers and drive technical alignment and influence across teams.

• BS/MS with 2-3 years of industry experience required

• Proven experience designing, deploying, and managing infrastructure on AWS (EC2, S3, RDS, etc.).

• Proficiency in scripting languages (e.g., Python) and compiled languages (e.g., C++, Go, Rust).

• Strong experience with Git and repository management.

• Excellent problem-solving skills and a proactive attitude, with the ability to anticipate needs and drive projects to completion.

• Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and influence technical decisions.

• Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines.

Senior Machine Learning Engineer - Infra

• BS/MS with 3-5 years of industry experience required

• Proven experience designing, deploying, and managing infrastructure on AWS (EC2, S3, RDS, etc.).

• Proficiency in scripting languages (e.g., Python) and compiled languages (e.g., C++, Go, Rust).

• Strong experience with Git and repository management.

• Demonstrated ability to lead technical projects from conception to completion and deliver high-quality, scalable, and reliable software.

• Excellent problem-solving skills and a proactive attitude, with the ability to anticipate needs and drive projects to completion.

• Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and influence technical decisions.

• Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines.

Preferred

• Extensive experience with large-scale ML model platforms and tools.

• Deep understanding and experience with PyTorch implementation, especially regarding scaling inference performance.

• A history of significant contributions to open-source projects or industry standards.