Genomics Deep Learning Engineer

Key Skills

C Programming, C++, Large Language Models - LLMs, Natural Language Processing (NLP), Neural Networks, Python Programming, PyTorch, TensorFlow

Job Description

NVIDIA is at the forefront of redefining healthcare by harnessing the power of GPU computing and AI to redefine data analysis in fields such as genomics and personalized medicine. We are on the lookout for hardworking and committed individuals to join our mission in integrating AI driven genomic solutions into mainstream healthcare. As a Genomics Deep Learning Engineer, you will be part of an innovative team dedicated to the development of deep learning algorithms tailored for genomics applications. This role offers the outstanding chance to define, implement, productize, and deliver innovative computing software that will have a global impact on genomics community. If you are driven by solving complex computational challenges in the genomics field, this role is tailor-made for you!

What you'll be doing:

• Develop and refine deep learning models and techniques for genomics analysis, including but not limited to DNA sequencing, variant calling, and model prediction.
• Innovate deep learning-based methodologies to enhance and apply advanced Large Language Models (LLMs), Graph Neural Networks, Graph Transformer Networks, and construct extensive multi-modal models in genomics.
• Design and implement machine learning techniques to tailor foundation models for downstream genomic specific tasks.
• Generate and manage datasets for large-scale machine learning, focusing on learning from genomics specific applications.
• Collaborate closely with product and hardware architecture teams to ensure flawless integration of research and development into NVIDIA products.
• Work in tandem with engineering and AI research teams to employ the latest technologies for scalable and innovative genomics analysis.

What we need to see:

• Bachelor's or Master's degree in Computer Science, Bioinformatics, or Computational Biology, or related field (or equivalent experience).
• 8+ years of relevant experience.
• Proficiency in C/C++ and Python, with a strong grasp of software design and programming principles.
• Background with Large Language Models (LLMs) and natural language processing (NLP), Generative AI and Foundation Models.
• Strong proficiency with modern frameworks such as PyTorch and TensorFlow, Experience with Large scale inferencing.
• Experience in building and implementing complex algorithms and data structures, with a focus on bioinformatics or genomics applications.
• Deep understanding of computer system architecture, operating systems, and the challenges associated with large-scale genomic data analysis.

Ways to stand out from the crowd:

• Ph. D. in Computer Science, Statistics, Bioinformatics, Computational Biology, or closely related fields.
• Hands-on experience in using LLM, Graph Neural Network, Graph Transformer Network particularly those applied to genomics data.
• Strong collaborative and interpersonal skills to effectively work and influence within a dynamic, technical environment.
• Ability to decompose complex requirements into step by step tasks and reuse available solutions to implement most of those.

Join our team where you'll play a pivotal role in crafting and building real-time efficient AI/ML solutions that underpin our triumphs in the fast-paced multifaceted and quickly growing genomics field. You will also be eligible for equity and benefits (https://www.nvidia.com/en-us/benefits/).

The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.