[Remote] Solution Architect – Drug Discovery at NVIDIA

United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Pharmaceutical, Life Sciences, Healthcare, TechBioIndustries

Requirements

MS or PhD (or equivalent experience) in Computer Science, Computational Biology, Computational Chemistry or Computational Physics, or related fields with strong applied experience in these domains
5+ years of work-related experience with hands-on expertise in AI/ML for healthcare or life sciences
Proven experience with Python and AI/ML frameworks (PyTorch, Langchain, or building custom framework) and application to scientific questions
Strong time-management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects
Motivated self-starter with an equal balance of strong problem-solving skills and customer-facing communication skills - especially in effectively presenting complex technical information
Must enjoy engaging with innovative individuals, continuous learning, and staying at the forefront of the field
Ways to stand out
Experience building, deploying, and optimizing agentic AI systems for healthcare and life sciences end-to-end including data ingestion, preprocessing, model training, agentic tool development, pipeline deployment and evaluation, especially for scientific software vendors and data platforms
Experience developing, training and customizing Transformer models for healthcare and life sciences applications, especially using libraries like Transformer Engine or Megatron-LM
Familiarity with AI deployment/inference technologies such as TensorRT, TRT

Responsibilities

Guide customers through the end-to-end process of GenAI adoption—from requirements gathering and proof-of-concept development to deployment, integration, benchmarking and ongoing optimization
Collaborate with our business/account team to identify technical needs, customer goals, and strategies
Enable customer adoption of NVIDIA technology by mapping our solutions to their use cases and driving positive relationships with our technology partners, making NVIDIA an integral part of end-user solutions
Keep up to date on AI advancements in drug discovery including agentic AI techniques, foundation models for protein, small molecules, and genomics, as well as relevant NVIDIA technology that enable this innovation
Design, develop, and optimize solutions tailored for healthcare and life science applications, such as AI scientists and autonomous lab or drug discovery
Engaging with developers, researchers, data scientists, IT managers, and senior leaders internally and externally to gain experience in various technical areas
Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles to simply working through hard problems with a customer on a whiteboard

Skills

GenAI

Large Language Models

LLMs

GPU

Machine Learning

High-Performance Computing

Drug Discovery

Protein Models

Genomics

Foundation Models

Agentic AI

Proof-of-Concept

Benchmarking

NVIDIA Technology

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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