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Remote Nvidia Engineering Jobs in Oregon (NOW HIRING)

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Remote Nvidia Engineering information

What is a Remote Nvidia Engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What are the key skills and qualifications needed to thrive as a Remote Nvidia Engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

What are the most commonly searched types of Nvidia Engineering jobs in Oregon? The most popular types of Nvidia Engineering jobs in Oregon are:
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Remote Nvidia Engineering jobs near you

Staff Applied Machine Learning Engineer (Remote - Anywhere in USA)

Legion Intelligence

OR • Remote

Other

Posted 11 days ago

Job description

Staff Applied Machine Learning Engineer (Remote - Anywhere in USA)

***US Citizenship or Greencard is required due to US Government contract requirements***

About us:

Let's be real, AI isn't magic; Legion was built to move beyond AI hype-delivering secure, reliable systems that work alongside the people tackling the world's most critical challenges.

Born from a Department of Defense partnership and trusted by leaders across government and enterprise, Legion embeds intelligence inside complex systems, unlocking data, accelerating human workflows, and strengthening mission-critical systems. We don't replace workflows-we optimize them, ensuring quality, efficiency, and reliability inside the platforms our partners already use.

With world-class collaborators like Palantir, Nvidia, HPE, and Oracle, we're building intelligent infrastructure that enhances human capability and drives impact at the edge and across a range of enterprises.

We're looking for bold thinkers and doers to join us in shaping the future of AI that's secure, grounded, and built to work.

Job Summary:

In this role, you will leverage your expertise in AI/ML engineering to design, develop, and deploy innovative machine learning and algorithmic solutions. 

If you are adept at building models that solve hard problems, we encourage you to apply. You will collaborate closely with platform engineers and product partners, bringing a strong product orientation to your ML work.

Responsibilities:

  • Lead the development of machine learning models and data-driven algorithms for high impact projects
  • Lead the design and development of complex systems involving knowledge graphs and advanced entity detection
  • Collaborate with product and platform teams to own ML solutions end-to-end
  • Understand the runtime complexity of algorithms and the cost to run ML models at a production scale
  • Clearly communicate modeling decisions, tradeoffs, and limitations to technical and non-technical stakeholders
  • Build, deliver, and maintain enterprise products, ensuring they meet high-quality standards while shipping fast
  • Take ownership of your work, from design to implementation and maintenance, and drive projects to successful completion
  • Support production systems, handling debugging challenges in distributed systems to ensure reliability and uptime
  • Adapt quickly, bringing in latest developments in AI and machine learning, and proactively apply this knowledge to drive innovation within the company

Required Skills and Qualifications:

  • US Citizenship or Greencard is required due to US Government contract requirements
  • Bachelor's or Master's degree in Computer Science, Machine Learning, NLP. PhD is preferred.
  • 10+ years of experience in ML engineering with a proven track record of building models for large-scale systems
  • Experience building and supporting knowledge graph and semantic representation systems
  • Proven experience designing, building, evaluating, and optimizing Agentic AI systems, including reasoning loops, tool use, orchestration patterns, context management
  • Strong communication skills and the ability to collaborate effectively with cross-functional teams
  • Comfortable supporting production systems and debugging challenges in distributed systems
  • Demonstrated effectiveness in using AI tooling to accelerate research and development workflows
  • Growth mindset and low ego- you're eager to pick up new tools and technologies, learn from others, and being open to changing course when it's right
  • Drive to foster a culture of collaboration, psychological safety, and technical excellence
  • Strong advocate for inclusion in technical discussions at all levels

Preferred Qualifications:

  • Start-up experience or comfort in 01 product environments.
  • Familiarity with Kubernetes is a plus.
  • Experience integrating machine learning models and data driven algorithms into larger system architectures.

Equal Opportunity Statement

Legion provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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