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 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 large language models and generative AI position us at the forefront of this revolutionary field.

With headquarters in Silicon Valley, California, and branch offices 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

• Conduct cutting‑edge research in AI, foundation models, and computational biology, improving existing models and exploring new methodologies to advance our AI capabilities in biology.
• Collaborate on designing and executing large‑scale experiments, analyzing complex datasets, and applying statistical techniques to validate the performance and robustness of AI systems.
• 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.

Qualifications

• 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).
• Strong coding skills with excellent proficiency in C/C++ and Python.
• Fluency in deep‑learning frameworks such as PyTorch (and/or JAX), Hugging Face (Datasets, Accelerate, Transformers, etc.), Megatron‑LM, DeepSpeed, etc.
• Solid understanding of GPU, CPU, or other AI accelerator architectures.
• Familiarity with LLM (and/or other foundation model) architectures—including attention mechanisms, state‑space models, Mixture of Experts, and training infrastructure (e.g., large‑scale GPU clusters).
• Experience improving ML accuracy using low‑precision formats.
• 1+ years of relevant industry experience.
• Derive great satisfaction from each percentage point of performance improvement.
• 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.
• Proficiency in Python with experience in GPU‑accelerated libraries such as CUDA and 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

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.