Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
CI/CD @ 3
Leadership @ 3
Mathematics @ 3
API @ 3
GPU @ 3
AI @ 3
HPC @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA BioNeMo is building the computational foundation for the next generation of biological discovery. We are looking for a hands-on technical manager to lead our MD Simulation Engineering team — a focused group whose mission is to enable biological simulation engines at scale.
You will lead a team of engineers building GPU-native simulation software the scientific community depends on. This role combines player and mentor responsibilities: maintain technical credibility throughout the group's efforts, guide architectural decisions, own the roadmap, coordinate dependencies with NVIDIA and external partners, and support team growth.
Responsibilities
- Lead, hire, and develop software engineers within a collaborative unit; build a culture of ownership, engineering excellence, and direct collaboration with researchers and authorities in the field.
- Define vision, strategy, and roadmap for the division's GPU-accelerated simulation software.
- Own end-to-end delivery across multiple workstreams; align partners, lead cross-team dependencies, and drive predictable execution.
- Partner with Applied Science teams to translate research prototypes into production-quality, benchmarked software.
- Build and maintain relationships with the molecular dynamics (MD) modeling community to ensure the team is delivering what the community needs.
- Drive engineering completion: code quality, CI/CD, multi-SKU validation, and documentation standards.
- Communicate progress, risks, and decisions clearly to stakeholders and senior leadership.
Requirements
- 8+ overall years of software engineering experience, including 3+ years being responsible for an engineering team with direct reports.
- Strong technical foundation in GPU computing and high-performance scientific software; ability to review builds, influence architectural directions, and maintain high engineering standards across the team's work.
- Experience shipping production GPU libraries, scientific computing software, or developer-facing APIs — experience taking prototypes to production that external developers depend on.
- Familiarity with molecular dynamics simulation concepts (force fields, electrostatics, neighbor lists, periodic boundary conditions) sufficient to engage credibly with colleagues and the MD simulator community.
- Proven record leading multi-functional dependencies, working across interpersonal boundaries without direct authority, and communicating technical progress clearly to senior leadership.
- BS/MS in Computer Science, Computational Science, Physics, Chemistry, or a related field, or equivalent experience.
Ways to Stand Out
- Shipped a GPU-accelerated scientific computing library or contributed/supplied to a major open-source MD simulation engine.
- PhD-level education or comparable experience in computational chemistry, biophysics, applied mathematics, or computer science with a focus on HPC or scientific computing.
- Experience with GPU compiler toolchains or kernel delivery mechanisms.
- Experience turning algorithmic research into shipped, benchmarked products.
- Active engagement in the MD simulation or computational chemistry community through publications, conference talks, or open-source contributions.
Compensation & Other Details
- Base salary range: 224,000 USD - 356,500 USD (final base salary determined by location, experience, and pay of employees in similar positions).
- Eligible for equity and benefits.
- Applications accepted at least until May 26, 2026. This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.