Solutions Architect - Healthcare and Life Sciences at NVIDIA

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Apr, 26

Salary

241500.0

Posted On

25 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Deep Learning, Machine Learning, Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics, Computer Science, Scientific Python, Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, Workflow Management

Industry

Computer Hardware Manufacturing

Description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is recruiting a Solutions Architect to innovate in AI-driven drug discovery within the biopharma industry. You will collaborate with researchers to accelerate breakthroughs by building robust data strategies and AI models on NVIDIA’s computing platform. This role focuses on designing scalable ETL pipelines, curating high-quality scientific datasets, and implementing advanced machine learning workflows. Our solutions architects are elite developers and scientists who thrive in a fast-paced environment, applying deep learning, machine learning, and high-performance computing to solve complex scientific challenges. Candidates should have strong domain expertise in computational sciences and life sciences, with significant data engineering and deep learning experience. If you are passionate about AI and computational science and have a background in life sciences or related fields, we invite you to help shape the future of healthcare with NVIDIA. What you will be doing: You will partner with researchers and scientists to develop a keen understanding of their data challenges and scientific goals, helping to define and deliver high-value data strategies that drive AI innovation. Staying up on the state of the art in Generative AI and data engineering for scientific applications. You will architect and implement high-performance ETL (Extract, Transform, Load) pipelines and data curation workflows to feed large-scale AI models on NVIDIA GPU supercomputers. Be an industry leader with a vision of integrating NVIDIA technology into the end-to-end data lifecycle—from raw scientific data ingestion to model training and inference. Building, optimizing, and deploying complex machine learning and deep learning training workflows, ensuring data efficiency and model performance at scale. What we need to see: MS or PhD in Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics, or Computer Science with strong applied experience in these domains (or equivalent experience). 3+ years of work-related experience in data science, machine learning engineering, or computational science. Proficient in scientific Python (Pandas, NumPy, Scikit-learn) and deep learning frameworks (PyTorch, TensorFlow). Experience with workflow management tools (e.g., Airflow, Nextflow) is essential. Strong background in molecular modeling, life sciences, and familiarity with biological data formats (e.g., SMILES, PDB, FASTA). Excellent communication skills, particularly in the presentation of highly technical data strategies. Must enjoy interacting with forward-thinking people and bridging the gap between data engineering and scientific research. Ways to stand out from the crowd: Demonstrated work in processing scientific data at scale (Terabyte/Petabyte scale) for cheminformatics, bioinformatics, or drug discovery. Experience preparing datasets for Large Language Models (LLMs), Generative AI, or geometric deep learning models in a scientific context. Experience in the biopharma industry or with customers/partners in the pharmaceutical domain, specifically with data governance and security. Published record of thought leadership in data science, AI, or a related industry segment. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until January 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. 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. #deeplearning NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Responsibilities

You will partner with researchers to develop data strategies that drive AI innovation and implement high-performance ETL pipelines. The role involves building and optimizing machine learning workflows to enhance data efficiency and model performance.