Full-Time
Research Scientist – PhD New College Grad
Posted on 4/18/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$168k - $264.5k/yr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
PhD
 AI & Machine Learning (2) |
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- Ph.D. or equivalent research experience in Computer Science/Electrical Engineering/Cognitive Science or related field.
- Excellent track record of publications in top-tier conferences (SIGGRAPH, CHI, HRI, ICRA, NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, CoG, ETRA, etc.).
- Experience with studying human behaviors in related application domains such as gaming, driving, interacting with robots, etc.
- Proficiency with Python, Rust, and/or C++.
- Experience with AI model training and evaluation frameworks, like PyTorch.
- Propose, research, prototype and test innovative research ideas.
- Publish at top conferences and patent novel inventions.
- Collaborate with other research team members, external researchers, and mentor interns.
- Create working interactive demonstrations to showcase your research ideas.
- Participate in technology transfer with engineers around NVIDIA as ideas "graduate" from research to product.
- Demonstrated public portfolio (e.g. repositories, OSS contributions, notebooks, packages, or technical blog posts with code).
- Experience with multi-node, multi-GPU training and inference workflows.
- Familiarity with and interest in modern deep learning models, including working with large-scale, multi-modal foundation models (such as recent LLMs, VLMs).
- A track record of applying human behavior models to machine learning applications, or applying machine learning to understand or model human behavior.
NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
Get referred to NVIDIA
See people who can refer or advise you
Simplify's Take
What believers are saying
- NVIDIA reported $81.6 billion quarterly revenue on August 2026, with data center at $75.2 billion.
- Goldman and BlackRock are building a $500 billion AI financing platform around NVIDIA hardware.
- Larsen & Toubro won NVIDIA’s India AI factory contract, expanding regional deployment capacity.
What critics are saying
- China export controls on May 31, 2026 still block Blackwell shipments to Chinese firms.
- Reuters on July 14, 2026 said NVIDIA cut Asia buyers, shrinking neocloud access.
- Beijing’s 2025 antitrust probe over Mellanox keeps a forced-remedy breakup threat alive.
What makes NVIDIA unique
- CUDA locks developers into NVIDIA’s software stack across every major AI cloud.
- Blackwell and Rubin roadmap keeps NVIDIA one generation ahead of rivals.
- NVIDIA controls chips, networking, and systems, not just standalone GPUs.
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Growth & Insights and Company News
6 month growth
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↓ -2%2 year growth
↓ -3%Nvidia has scaled back plans to guarantee data centre projects, according to a report. The move comes as OpenAI's Stargate project with Oracle and SoftBank Group advances a $500 billion US AI infrastructure initiative expected to exceed 9 gigawatts by 2029. Seven US sites are under development, with 0.3 gigawatts already operating in Abilene, Texas. Legal analysts noted that large AI infrastructure commitments can involve contingent or off-balance-sheet risk. Stargate's expansion continues, with related sites using bond, private-credit, and special-purpose vehicle financing. Analysts suggest any Nvidia pullback would more likely alter the financing mix rather than halt construction. The report did not detail Nvidia's commitment.
Jim Cramer highlighted NVIDIA's dominant position in the data centre market on his Mad Money show, citing CoreWeave's strong quarterly results as evidence of the chips' enduring value. CoreWeave CEO Michael Intrator demonstrated that older NVIDIA GPUs retain or even appreciate in value, with some nine-year-old chips remaining highly sought after. NVIDIA reported record fiscal first-quarter revenue of $81.6 billion, up 85% year-over-year. Data centre compute revenue reached $60.4 billion, whilst networking revenue surged 199% to $14.8 billion. CEO Jensen Huang described the global AI infrastructure buildout as unprecedented. Morningstar analyst Brian Colello maintained a fair value estimate of $280 for the stock, acknowledging concerns about complex financing arrangements but affirming underlying chip demand remains strong.
Agility Robotics is going public through a SPAC merger with Churchill Capital Corp XI at a $2.5bn valuation, significantly below private humanoid robotics rivals. The Oregon-based company expects to raise over $620m in proceeds, with the merger closing in Q4 2026. The valuation trails competitors substantially. Apptronik raised funds at above $5bn, whilst Figure AI closed Series C funding at a $39bn post-money valuation. Investors cite Agility's relatively weaker position on deployments and technology as justification for the discount. Agility has booked over $300m in multi-year revenue tied to roughly 1,000 robots, with 65,000 operational hours across nine customer facilities. However, analysts caution this backlog involves contracts for robots still in development, with cancellation provisions. Industry experts warn against overvaluing humanoid robotics relative to established automation technologies. The company's challenge lies in converting technological promise into repeatable deployments and demonstrable ROI whilst competing against proven automation alternatives already generating substantial revenue.
Goldman Sachs is helping Nvidia mobilise more than $500 billion for AI infrastructure financing, according to Reuters. The investment bank is discussing structures with insurers, banks, and asset managers to create independent financing platforms for Nvidia-powered systems. The initiative, announced on 10 August, brings together Goldman, Apollo, BlackRock, Blackstone, Brookfield, and KKR. Nvidia could backstop up to $125 billion, or 25%, of potential transactions. Goldman's asset-management business could provide junior capital and private credit, whilst its investment bank could place debt with private-credit funds and public bond investors. The strategy aims to transform GPUs and AI systems into an investable infrastructure asset class. This could expand the addressable market by removing capital constraints on AI infrastructure deployment as Nvidia's Data Center revenue jumped 92% to $75.2 billion in the first quarter of fiscal 2027.
Jim Chanos has warned that CoreWeave's competitive advantage depends entirely on Nvidia, which effectively controls the neocloud business model. The short-seller argued that neoclouds are "financial conduits, not technology companies" and that Nvidia could undermine their position by changing GPU allocation policies or raising prices. Chanos's comments followed a Damsker report challenging CoreWeave CEO Mike Intrator's claim that customers choose the company for product quality. The report argued that CoreWeave simply buys expensive GPUs, builds data centres, and rents computing capacity — a "scarcity claim, not a preference claim." CoreWeave reported $2.58 billion in second-quarter revenue, more than double the previous year, with revenue backlog reaching $104.2 billion. The company raised its 2026 capital spending forecast to between $35 billion and $39 billion.