SENIOR/PRINCIPAL AI ENGINEER

Description.

We seek a highly motivated Senior/Principal AI Engineer to join the BRAID department (Biology
Research | AI Development) within our Computational Sciences organization in Genentech
Research and Early Development (gRED).
Our department is dedicated to leveraging AI to accelerate drug discovery and target discovery
efforts. Our focus spans large-scale foundation models across biochemical modalities,
multi-modal reasoning, and autonomous agent design, with a strong emphasis on scientific
discovery, drug development, and complex decision-making pipelines.
The successful candidate will contribute to developing, deploying, and scaling foundation
models and intelligent agents across different modalities for complex decision-making pipelines.
They will work at the intersection of deep learning and large-scale optimization, with a focus on
scaling training/inference, model deployment, and MLOps. The successful candidate will work in
an exciting and multidisciplinary environment alongside AI scientists, AI engineers, and
computational biologists/chemists in a research-focused team dedicated to advancing the
frontier of AI and its impact on drug discovery.
Prior experience in biology/chemistry is not required for this role.
The role
– Design, optimize, and deploy cutting-edge deep learning models (e.g. large language
models, multi-modal transformers, etc.) and data pipelines.
– Optimize and scale model and data pipelines for performance and accuracy.
– Monitor and maintain deployed models, ensuring the best performance in applications.
– Collaborate with cross-functional teams to translate novel ML methods into impactful
applications for drug discovery and target discovery.
Who you are

MUST HAVES

– Master’s/ PhD degree in Computer Science, Machine Learning, Data Science, or a
related field.
– Technical skills:
– Strong foundations in data structures, algorithms, and software engineering
principles.
– Demonstrated experience in deep learning (e.g., previous projects or
publications).
– Excellent Python and PyTorch programming skills.
– Demonstrated experience with MLOps, model deployment (e.g., Triton, ONNX),
and API-based AI systems.
– Experience with large-scale distributed training and/or multi-GPU/cloud
infrastructure (e.g., Ray, FSDP, DeepSpeed, TPU).
– Passionate about developing scalable, efficient, and well-documented software.
– Hands-on experience with LLMs (e.g., in-context strategies or finetuning) and
agent-based systems is a plus.
– Prior experience in drug discovery and biomedical AI is not required but is a plus.
– Strong communication and collaboration skills with the ability to effectively communicate
technical concepts to both technical and non-technical audiences.
– Take full ownership of challenges from start to finish and proactively acquire any
necessary knowledge to drive solutions forward