Senior Machine Learning Engineer - BRAID Genomics

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

Genentech is seeking an exceptional Senior Machine Learning Engineer to join the BRAID (Biology Research | AI Development) team within our Computational Sciences organization. This role will focus on developing, optimizing and deploying novel machine learning methods with a strong emphasis on foundation models for genomics data modalities. You will build and productionize machine learning systems and foundation models for regulatory genomics, enabling sequence-to-function modeling, variant effect predictions, and nucleic acid design.

In this role, you will:

• Training, fine-tuning, evaluation, benchmarking, deployment of DNA/RNA sequence-to-function models.

• Design scalable data and training pipelines (distributed training, efficient dataloading, reproducibility, experiment tracking).

• Build and maintain production-grade inference systems (APIs/SDKs, latency/cost optimization, reliability, monitoring).

• Establish engineering best practices for ML codebases: CI, unit/integration tests, model versioning, documentation, and code reviews.

• Collaborate closely with computational biologists, wet-lab partners, and platform teams to define requirements, success metrics, and adoption pathways.

Who you are

• PhD with 5+ years professional software engineering experience (or equivalent), including ownership of production services or ML platforms.

• Strong Python engineering skills (clean architecture, packaging, testing, CI, performance profiling).

• Deep experience with PyTorch, including training workflows and debugging numerical/performance issues.

• Experience with modern deep learning for sequences or high-dimensional biological data (transformers, representation learning, generative modeling).

• Familiarity with regulatory genomics or functional genomics data and evaluation (e.g., expression/splicing/chromatin assays; variant effect prediction).

• Excellent communication skills; ability to translate scientific needs into reliable software and measurable deliverables.

Preferred Qualifications

• Experience with long-context sequence modeling and established genomic frameworks (e.g., Enformer/Borzoi-style models).

• Distributed training and systems experience (multi-GPU, DDP/FSDP, mixed precision; GPU profiling/optimization).

• MLOps experience (model registry, experiment tracking, deployment pipelines, monitoring/drift).

• Experience with single-cell and scverse ecosystem tools (scanpy/anndata, etc.).
  Publications or open-source contributions in ML + genomics are a plus.

Relocation benefits are NOT available for this job posting

The expected salary range for this position, based on the primary location of California, is $167,400 - 310,800. 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

#ComputationCoE

#tech4lifeComputationalScience

#tech4lifeAI

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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