Headquartered in Silicon Valley, we are a newly established start-up where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of generative AI. Our team comprises leading minds and innovators in AI and biological science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine.
We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBM), we are pioneering a new era of biomedicine, with our LBM training leading to ground-breaking advancements and a transformative approach to healthcare. Our robust R&D team and leadership in LLMs and generative AI position us at the forefront of this revolutionary field. With headquarters in Silicon Valley, California, and a branch office in Paris and Abu Dhabi, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.
Job Description:
You will work with the team to conduct cutting-edge research in AI, foundation models, and computational biology. Your primary tasks will include improving existing models and exploring new methodologies to advance our AI capabilities in biology
You will collaborate with the team on designing and executing large-scale experiments, analyzing complex datasets, and applying statistical techniques to validate the performance and robustness of AI systems
Additionally, you will work closely with AI/machine learning researchers and computational biologists to develop Genbio AI’s state-of-the-art biology foundation models and drive the research agenda to generate impact
Qualification:
Currently enrolled in a full-time masters or PhD (preferred) program in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field (preferably in the United States)
A strong coder with excellent skills in C/C++ and Python
Fluent in deep learning frameworks like PyTorch (and/or JAX), Hugging Face (Datasets, Accelerate, Transformers, etc.), Megatron-LM, DeepSpeed, etc
Have a solid understanding of GPU, CPU, or other AI accelerator architectures
Familiar with LLM (and/or other foundation model) architectures (such as attention mechanisms, state-space models, MoE, etc.) and training infrastructure (e.g., large-scale GPU clusters)
Have experience improving ML accuracy using low-precision formats
Have 1+ years of relevant industry experience
Derive a great deal of satisfaction from every percentage point of performance improvement
Have experience writing and optimizing compute kernels using CUDA or similar languages
Nice to Have:
Current PhD in Computer Science and Engineering with a specialization in Computer Architecture, Parallel Computing, Compilers, or other systems
Co-optimizing computing infrastructure and deep learning frameworks for optimal performance on specific workloads. Identify and resolve performance bottlenecks through profiling and system analysis
Experience collaborating with data scientists and machine learning engineers to integrate distributed training capabilities into GenBio AI’s model development and deployment frameworks
Proficient in Python with experience in GPU-accelerated libraries (e.g., CUDA, cuDNN)
Knowledge of performance profiling and optimization tools for HPC and deep learning
Join us as we embark on this journey to redefine the future of biology and medicine.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security’s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov.
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.
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