Senior Machine Learning Scientist sf, ca
$200k - $275kESR Healthcare
Job Description:
Senior Machine Learning Scientist sf, ca Senior Machine Learning Scientist, 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 - Essential PhD or equivalent practical experience in a technical field. A proven track record of developing and applying deep learning methods, including experience with modern architectures such as transformers, state-space models, graph neural networks or diffusion-based generative models. Proficiency with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow) and core scientific computing libraries (e.g., NumPy, SciPy, Pandas). A genuine enthusiasm for applying cutting-edge ML research to real-world biological problems and a bias towards action. Qualifications - Nice to have Prior experience with ML applied to problems in biology or chemistry. Familiarity with multimodal modeling, contrastive learning or self-supervised learning. Experience with large scale distributed ML techniques (e.g., FSDP, TP, dMoE, flash attention) Key Responsibilities Develop and apply machine learning techniques towards building multimodal foundation models that bridge the chemical and biological domains, i.e.: integrate models of chemical structure, target protein sequence and whole transcriptome scRNAseq. Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to our problems and datasets. Collaborate with our team of biologists and engineers in cross-functional pods to test novel ML-driven hypotheses. 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. $200,000 - $275,000 a year 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Working Place: San Francisco, California, United States Company : ESR Healthcare
Senior Machine Learning Scientist sf, ca Senior Machine Learning Scientist, 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 - Essential PhD or equivalent practical experience in a technical field. A proven track record of developing and applying deep learning methods, including experience with modern architectures such as transformers, state-space models, graph neural networks or diffusion-based generative models. Proficiency with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow) and core scientific computing libraries (e.g., NumPy, SciPy, Pandas). A genuine enthusiasm for applying cutting-edge ML research to real-world biological problems and a bias towards action. Qualifications - Nice to have Prior experience with ML applied to problems in biology or chemistry. Familiarity with multimodal modeling, contrastive learning or self-supervised learning. Experience with large scale distributed ML techniques (e.g., FSDP, TP, dMoE, flash attention) Key Responsibilities Develop and apply machine learning techniques towards building multimodal foundation models that bridge the chemical and biological domains, i.e.: integrate models of chemical structure, target protein sequence and whole transcriptome scRNAseq. Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to our problems and datasets. Collaborate with our team of biologists and engineers in cross-functional pods to test novel ML-driven hypotheses. 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. $200,000 - $275,000 a year 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Working Place: San Francisco, California, United States Company : ESR Healthcare
Vacancy posted 11 hours ago
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