Research Engineer Intern

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 biologyYou 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 systemsAdditionally, 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 impactQualification:

Currently enrolled in a full-time master's 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 PythonFluent in deep learning frameworks like PyTorch (and/or JAX), Hugging Face (Datasets, Accelerate, Transformers, etc. ), Megatron-LM, DeepSpeed, etcHave a solid understanding of GPU, CPU, or other AI accelerator architecturesFamiliar 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 formatsHave 1+ years of relevant industry experienceDerive a great deal of satisfaction from every percentage point of performance improvementHave experience writing and optimizing compute kernels using CUDA or similar languagesNice to Have: Current PhD in Computer Science and Engineering with a specialization in Computer Architecture, Parallel Computing, Compilers, or other systemsCo-optimizing computing infrastructure and deep learning frameworks for optimal performance on specific workloads.

Identify and resolve performance bottlenecks through profiling and system analysisExperience collaborating with data scientists and machine learning engineers to integrate distributed training capabilities into GenBio AI’s model development and deployment frameworksProficient in Python with experience in GPU-accelerated libraries (e. g. , CUDA, cuDNN)Knowledge of performance profiling and optimization tools for HPC and deep learningJoin 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.