Find Jobs
Find Jobs Near You – Available Work in Your Location
Skip to job details
G
Genentech
Principal Scientist, SOP & Workflow Automation Champion, AI for Drug Discovery (AIDD)
Career Insights for Computational Biologist
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on California data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Computational Biologist uses biological data to develop models to better understand biological systems. Conducts analysis using computational and mathematical methods and large data sets.
$137,317 / year median in California
+8% projected growth
Job Description
Back to search results Previous job Next job Apply Now Save job
JOB DESCRIPTION
The Position 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 the 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. The Opportunity At Roche's AI for Drug Discovery (AIDD) group within the Computational Sciences Center of Excellence, we are architecting a vision for end-to-end computational drug discovery. Today, drug discovery workflows are fragmented—different models for different modalities, disconnected processes across teams, manual handoffs between discovery and development. We are building a unified, modular system where machine learning methods integrate seamlessly into executable, agentic workflows that empower scientists across our organization to discover better medicines faster. This is a critical moment. We have developed novel machine learning capabilities for large molecule discovery, but translating those capabilities into scalable, operationalized workflows at the organizational level requires both scientific credibility and strategic engineering acumen. We're looking for an exceptional Principal Scientist who can architect how our computational models become standard operating procedures (SOPs) and automated workflows that portfolio teams actually use, depend on, and trust. Drug discovery is moving toward end-to-end computational pipelines. Today, our ML methods exist in silos—powerful but disconnected from operational workflows. The scientist who can bridge that gap—who designs the systems that make models actionable, scalable, and trustworthy—will fundamentally accelerate how medicines are discovered. That's this role. In this role, you will: Design computational workflow architecture that operationalizes modular ML components into scalable, reproducible, and agentic-ready systems Lead the development and standardization of SOPs for model integration, data pipelines, and workflow execution across gRED and pRED Partner strategically with Roche's platform engineering teams to implement workflows at scale Architect data integration with Roche's centralized data infrastructure (DDC), ensuring seamless model-data-workflow loops Collaborate with the modeling team to translate research-stage models into production-ready components with clear interfaces, performance benchmarks, and failure modes Navigate complex stakeholder environments , including portfolio teams, platform organizations, and technology development groups, to align on standards and drive adoption Lead and mentor engineers and scientists on workflow design, automation best practices, and computational architecture Who you are Technical Foundation PhD in Computer Science, Computational Biology, Bioinformatics, or related field, or equivalent advanced experience (8+ years building computational systems) Deep expertise in workflow orchestration, data pipeline design, and software architecture (not just machine learning) Proven experience designing systems that integrate heterogeneous data sources, models, and processes at scale Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX); familiarity with workflow tools (Nextflow, Snakemake, Airflow, or similar) Understanding of software engineering practices: version control, testing, documentation, CI/CD pipelines Experience in Life Sciences / Drug Discovery Demonstrated experience working at the intersection of computational methods and experimental biology Understanding of drug discovery workflows: what scientists actually need, where handoffs break down, how to design for usability Track record of translating research code into production systems that real teams use Experience working across technical and non-technical stakeholders (biology, chemistry, engineering) Leadership & Collaboration Proven ability to lead complex, cross-functional initiatives involving multiple teams and organizations Track record of driving adoption of new standards, tools, or processes in larger organizations Strong communication skills: can explain complex technical concepts to diverse audiences and build consensus First-author publications or equivalent evidence of research contributions Strategic Thinking You see the gap between "research works in a paper" and "research works at scale in an organization" You understand how to design systems for reliability, debuggability, and adoption You can balance scientific rigor with pragmatic engineering constraints Relocation benefits are NOT available for this job posting The expected salary range for this position, based on the primary location of California, is $201,300- 373,800.
JOB FACTS
Job Sub Category Artificial Intelligence & Machine Learning Schedule Full time Job Type Regular Posted Date Aug 5th 2026 JobID 202608-120343
Apply Now Save job Profile recommendations See more Show less See next See even more No recommendations found Similar Jobs Machine Learning Engineer, Infra, AI for Drug Discovery Available in 2 locations Category Data Science & AI / ML Save Machine Learning Engineer, Infra, AI for Drug Discovery 202607-120009 Machine Learning Scientist/Senior Machine Learning Scientist- Synthesis Planning and Optimization, AI for Drug Discovery Available in 2 locations Category Data Science & AI / ML Save Machine Learning Scientist/Senior Machine Learning Scientist
- Synthesis Planning and Optimization, AI for Drug Discovery 202606-115542 Machine Learning Scientist/Senior Machine Learning Scientist
- Agents for Applied Small Molecule Drug Design, AI for Drug Discovery Available in 2 locations Category Data Science & AI / ML Save Machine Learning Scientist/Senior Machine Learning Scientist
- Agents for Applied Small Molecule Drug Design, AI for Drug Discovery 202606-115525 Senior Scientist, Antibody Developability/Biophysics & Portfolio Support, AI for Drug Discovery (AIDD) Location South San Francisco, California, United States of America Category Data Science & AI / ML Save Senior Scientist, Antibody Developability/Biophysics & Portfolio Support, AI for Drug Discovery (AIDD) 202608-120346 Software Development Engineer/Senior Software Development Engineer, Agentic Systems, AI for Drug Discovery Available in 2 locations Available in 2 categories Save Software Development Engineer/Senior Software Development Engineer, Agentic Systems, AI for Drug Discovery 202607-118950 Senior Machine Learning Scientist, AI for Biology & Translation (AIBT) Location South San Francisco, California, United States of America Available in 2 categories Save Senior Machine Learning Scientist, AI for Biology & Translation (AIBT) 202607-119719 Senior/Principal Machine Learning Scientist, Perturbation Biology, AI Biology & Translation (AIBT) Location South San Francisco, California, United States of America Available in 2 categories Save Senior/Principal Machine Learning Scientist, Perturbation Biology, AI Biology & Translation (AIBT) 202606-114787 Senior Machine Learning Scientist, Foundational ML, AI for Biology & Translation (AIBT) Location South San Francisco, California, United States of America Available in 2 categories Save Senior Machine Learning Scientist, Foundational ML, AI for Biology & Translation (AIBT) 202606-117077 Principal Scientist, Portfolio & gRED Interface-Biologics, AI for Drug Discovery (AIDD) Location South San Francisco, California, United States of America Category Data Science & AI / ML Save Principal Scientist, Portfolio & gRED Interface-Biologics, AI for Drug Discovery (AIDD) 202608-120345 See more See less See next See even more No recommendations found Get notified for similar jobs Sign up to receive job alerts Email• I hereby consent to the processing of my personal data for the purpose of receiving job alerts as outlined in the Privacy Notice.
- By proceeding, I understand that my personal data will be processed in accordance with the Company Data Privacy Policy.