Description
Senior Machine Learning Engineer
Team: Machine Learning
Location: South San Francisco
Workplace Type: onsite
About Tahoe Therapeutics
Tahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery, one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world’s largest in vivo single-cell perturbation atlas and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response.
By combining cutting-edge machine learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster and bring them to more patients who need them.
Your role
With Tahoe-100M, we solved one of the fundamental bottlenecks in building a virtual model of the cell: generating massive, perturbation-rich, single-cell datasets that capture real biological causality. With Tahoe-x1, we removed the second bottleneck: creating a modern platform for rapid iteration on model architectures and designs in a cost-efficient manner and at scale. At Tahoe, we embody a simple philosophy: build in the open, shoot for the moon, and we’re looking for people who want to push the frontier of what’s possible.
As a Senior Machine Learning Engineer, you will play a leading role in designing the next generation of foundation models of gene regulatory networks powered by Tahoe’s large scale single-cell datasets such as Tahoe-100M and beyond. This role is well-suited for someone with a strong background in machine learning and statistics, and an interest in applying cutting-edge breakthroughs in ML to meaningful problems in drug discovery. We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery.
Qualifications - Required
- Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience.
- Exceptional engineering skills to iterate quickly on data processing and training pipelines
- Experience in building, testing, training, and deploying modern neural network architectures such as Transformers.
- Experience with frameworks like PyTorch, Tensorflow, Keras, JAX and the ability to write hardware optimized code for distributed training
Qualifications - Desirable
- Experience with distributed deep learning using frameworks such as HF Accelerate, Deepspeed, Composer, TorchTitan, Megatron etc.
- Experience with training large neural networks on multiple compute nodes.
Key Responsibilities
- Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to train AI virtual cell models on our massive single cell datasets.
- Work together with ML Scientists to develop the next generation of compute optimized models like Tahoe-x1.
Benefits
- Unlimited Paid Time Off (PTO).
- Monthly Lunch budget
- One-time Office set up budget
- US Employees: HMO Kaiser Platinum and PPO Anthem Gold medical as well as vision and dental plans for both the employee and dependents.
This position requires on-site presence at our South San Francisco office a minimum of three days per week.
We welcome applicants who require visa sponsorship and provide work authorization support for qualified candidates.
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