Machine Learning Engineer

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 Genentech Computational Sciences Center of Excellence (CoE), we're looking for a motivated Machine Learning Engineer to join us in developing innovative solutions for protocol generation, review, and AI-based search platforms. In this role, you'll work closely with key stakeholders to deliver impactful machine learning solutions that benefit our broader R&D community.

As a Machine Learning Engineer you will play a crucial role in crafting and implementing machine learning models that drive two of our internal R&D solutions: a search and insights platform tailored to our data ecosystem and a protocol generation and review platform that streamlines key research workflows. Working closely with researchers, scientists, and engineers, you will bring a harmonious approach and technical rigor to projects that fulfill our scientific teams' needs. This role is ideal for someone passionate about applying machine learning to improve internal solutions that directly enhance research and development.

The Opportunity:

• Design, develop, and deploy cloud-first, API-driven machine learning applications for data search, insights, and protocol generation and review platforms.

• Leverage large language models (LLMs) to improve contextual search, data retrieval, and scientific research efficiency through advanced prompt engineering, retrieval augmented generation, and fine-tuning techniques.

• Develop and refine LLMs tailored for protocol generation and review workflows, driving innovation in GenAI applications to streamline R&D processes.

• Collaborate with data engineers, software engineers, and architects to integrate ML models effectively within the internal data ecosystem.

• Monitor, validate, and optimize ML applications to ensure high-quality outputs, performance scalability, and a seamless user experience.

• Partner with research teams to identify needs, exchange insights, and deliver solutions that address evolving R&D requirements.

Who You Are:

• Hold a Bachelor's, Master’s degree or PhD in Computer Science, Data Science, Applied Mathematics, Bioinformatics, or a related quantitative field, with 2-4 years of experience in deploying machine learning applications at scale, preferably in R&D or data-intensive environments.

• Will be proficient in Python, with hands-on experience using modern frameworks for deep learning and GenAI, such as PyTorch, Hugging Face Transformers, LangChain, or Llama-Index.

• Good understanding of machine learning algorithms, model evaluation techniques, and performance optimization, with a knowledge of deploying LLMs in data-intensive settings.

• Skilled in cloud platforms (AWS, GCP, Azure), version control systems (Git, DVC, MLflow), CI/CD pipelines, and SQL for relational database management.

• Be a collaborative problem-solver with a strong sense of ownership, capable of partnering with interdisciplinary teams to deliver impactful solutions.

• Someone who is continuously updated on advancements in LLMs and GenAI, with a passion for applying these technologies to drive efficiencies in R&D workflows.

Preferred:

• A public portfolio of projects available on GitHub/GitLab.

• A record of scientific excellence, as evidenced by at least one publication in a scientific journal or conference.

Onsite presence on our South San Francisco campus is expected for at least 3 days a week.

Relocation benefits are available for this job posting.

The expected salary range for this position based on the primary location of California is $134,100 - $249,100 of hiring range.  Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.  A discretionary annual bonus may be available based on individual and Company performance.  This position also qualifies for the benefits detailed at the link provided below.

Benefits

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Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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