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Nvidia Research Jobs (NOW HIRING)

Nvidia

Principal Graphics Developer Tools Engineer

Seattle, WA · On-site

$159K - $196K/yr

You will create and lead new strategic initiatives, partnering closely with NVIDIA Research, GPU Architecture, Driver, SDK, and Developer Technology teams to evaluate emerging technologies, prototype ...

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Nvidia Research information

What is an Nvidia Research job?

An Nvidia Research job involves conducting cutting-edge research in areas like artificial intelligence, computer graphics, and high-performance computing. Researchers work on innovative projects that push the boundaries of technology, often collaborating with academia and industry partners. These roles typically require expertise in machine learning, deep learning, hardware acceleration, or related fields. Team members publish papers, develop prototypes, and contribute to Nvidia's long-term technological advancements.

What are the key skills and qualifications needed to thrive in the Nvidia Research position, and why are they important?

Excelling in Nvidia Research typically requires a PhD or advanced degree in computer science, electrical engineering, or a related field, with strong expertise in machine learning, computer vision, and deep learning algorithms. Familiarity with programming languages such as Python and C++, and experience using frameworks like TensorFlow or PyTorch, as well as CUDA for GPU computing, are also important. Excellent problem-solving abilities, creativity, and effective collaboration and communication skills help set candidates apart. These skills are crucial for conducting innovative research, collaborating with multidisciplinary teams, and advancing the field of AI and graphics technology.

What opportunities for career growth and advancement are available within Nvidia Research?

Nvidia Research offers a dynamic environment where researchers can grow by taking on increasingly complex projects, publishing groundbreaking work, and collaborating with world-class experts. Many team members advance to senior and principal researcher roles or transition into leadership positions overseeing multi-disciplinary research initiatives. Nvidia also encourages continuous learning through conferences, workshops, and internal seminars, which further support professional development. As the company continues to expand its research footprint, there are ample opportunities to shape new areas of innovation and make a lasting impact on both the organization and the industry.

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Nvidia Research jobs near you
AI Security Engineer supporting Nvidia

AI Security Engineer supporting Nvidia

Sustainable Talent

Santa Clara, CA • On-site, Remote

$90 - $130/hr

Full-time

PTO

Posted 3 days ago

Job description

Sustainable Talent is partnering with Nvidia a global leader who's been transforming computer graphics, PC gaming, and accelerated computing for over 25 years. We are looking for Generative AI Security Engineer to support our client's team based out of in Santa Clara, CA with remote/ hybrid work options.

This is a full-time (W-2) contract role. We offer competitive pay $90/hr - $130/hr based on factors like experience, education, location, etc. and provide full benefits, PTO, and amazing company culture!

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams, focused on AI Safety for LLMs, including multi-lingual, multi-modal, and reasoning models. We value expertise in data science paired with a robust data engineering foundation. This role is directed at assessing, and improving the safety and inclusivity of our LLM models in a scalable fashion. We seek someone proficient in programming and scripting for comprehensive data manipulation, analysis, and model fine-tuning. We believe in proactive problem-solving, minimal supervision, and being exceptional teammates who collaborate, think, and learn as one unit. Let's make a difference together!

What you'll be doing:

  • Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness. These LLM models can be txt-to-txt or multimodal-to-txt.
  • Develop datasets for training LLM models with SFT and RL techniques, for Content Safety, ML Fairness, Security and more.
  • Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems.
  • Define and track key metrics for responsible LLM behavior and usage.
  • Follow the best practices of automation, monitoring, scale, safety.
  • Contribute to our repositories and develop safety tools to help ML teams be more effective.
  • Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets.
  • Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.
  • Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

What we need to see:

  • Bachelor's or Master's Degree in Computer Science or related field or equivalent experience.
  • 2+ years of work experience as a Machine Learning Engineer or Deep Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions.
  • Strong programming skills in languages such as Python. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Proficiency in data manipulation, analysis, and visualization using tools like NumPy and pandas.
  • Deep understanding of machine learning algorithms, statistical models, and data structures.
  • Familiarity with software development practices and version control systems (e.g., Git).
  • Good at problem solving and analytical ability.
  • Excellent collaboration and communication skills.

Ways to stand out from the crowd:

  • Experience with GenAI Security including Prompt Injection Stability, Model Extraction, Confidentiality/Data Extraction, Integrity, Availability and Adversarial Robustness.
  • Experience with one or more of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application.
  • Experience with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs (Vision Language Model) or any-to-text
  • Experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance.
  • Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research and publication experience.

Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.

Apply