Genomics Deep Learning Engineer

Are you passionate about utilizing cutting-edge technology to advance the field of genomics? Do you have a strong background in deep learning and a keen interest in leveraging it for genomic research? If so, then we have an exciting opportunity for you to join our team at NVIDIA as a Genomics Deep Learning Engineer.As a leading technology company, NVIDIA is revolutionizing the way genomics research is conducted through the use of deep learning. We are seeking a highly skilled and motivated engineer to join our team and help us drive innovation in this rapidly growing field. In this role, you will have the opportunity to work with state-of-the-art tools and technologies to develop and implement deep learning solutions for genomic analysis.The ideal candidate will have a strong background in genomics and deep learning, as well as a passion for solving complex problems. If you are a self-starter with a strong drive for innovation and a desire to make a significant impact in the world of genomics, then we want to hear from you. Join us at NVIDIA and be a part of a dynamic team that is shaping the future of genomic research.

1. Research and Develop Deep Learning Solutions: Utilize your expertise in deep learning and genomics to research and develop cutting-edge solutions for genomic analysis.
2. Implement State-of-the-Art Tools and Technologies: Stay current with the latest tools and technologies in deep learning and genomics, and implement them to advance our research.
3. Collaborate with Cross-Functional Teams: Work closely with cross-functional teams, including biologists, data scientists, and software engineers, to develop and implement deep learning solutions for genomic analysis.
4. Conduct Data Analysis and Model Training: Use your knowledge of genomics and deep learning to analyze large genomic datasets and train deep learning models to extract meaningful insights.
5. Drive Innovation: Keep up-to-date with the latest advancements in the field of genomics and deep learning and proactively bring new ideas and solutions to the team.
6. Troubleshoot and Debug: Troubleshoot and debug any issues that arise during the development and implementation of deep learning solutions.
7. Document and Communicate Results: Effectively communicate and document the results and findings of your deep learning research and development to both technical and non-technical stakeholders.
8. Stay Compliant with Regulatory Standards: Ensure that all deep learning solutions and processes are compliant with regulatory standards and guidelines.
9. Mentor and Guide Junior Team Members: Provide mentorship and guidance to junior team members to help them grow and develop their skills in deep learning and genomics.
10. Continuously Learn and Improve: Proactively seek out learning opportunities to continuously improve your skills and knowledge in the field of genomics and deep learning.

According to JobzMall, the average salary range for a Genomics Deep Learning Engineer in Santa Clara, CA, USA is $120,000 - $170,000 per year. This may vary depending on factors such as experience, education, and the specific company or organization the engineer is employed by.

NVIDIA Corp. designs and manufactures computer graphics processors, chipsets, and related multimedia software. The company operates through two segments: Graphics Processing Unit and Tegra Processor. The Graphics Processing Unit segment includes sales of the company's GeForce discrete and chipset products that supports desktop and notebook PCs plus license fees from Intel and sales of memory products. The Tegra Processors segment provides processors that deliver superior visual and multimedia experience on tablets, smart phones and gaming devices while consuming minimal power.