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Nvidia Engineering Jobs in Pittsburgh, PA (NOW HIRING)

Synopsys Inc

HPC Software Engineer

Canonsburg, PA · On-site

Synopsys Inc is the leader in engineering solutions from silicon to systems, enabling customers to ... Intel VTune, NVIDIA Nsight, or similar, and translate findings into actionable performance ...

Cmu

Autonomy Engineer

Pittsburgh, PA · Hybrid

We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense ... Experience with physics-based simulators such as NVIDIA's Issac Sim is required. * Robotics ...

Motional

Senior Systems Performance Engineer

Pittsburgh, PA · Hybrid

$101K - $138K/yr

Communicate findings clearly and provide actionable recommendations to cross-functional engineering ... Experience with the NVIDIA DRIVE AGX platform or DriveOS ecosystem. * Familiarity with Bazel and ...

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All JobsNvidia Engineering JobsNvidia Engineering Jobs in Pittsburgh, PA

Nvidia Engineering information

See Pittsburgh, PA salary details

$45.1K

$142.6K

$168.9K

How much do nvidia engineering jobs pay per year?

As of Aug 28, 2026, the average yearly pay for nvidia engineering in Pittsburgh, PA is $142,582.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,100.00 and $168,000.00 per year, depending on experience, location, and employer.

What is an Nvidia engineer?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

What types of projects do Nvidia engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

What are the key skills and qualifications needed to thrive as an Nvidia engineer, and why are they important?

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What are popular job titles related to Nvidia Engineering jobs in Pittsburgh, PA?

For Nvidia Engineering jobs in Pittsburgh, PA, the most frequently searched job titles are:

What job categories do people searching Nvidia Engineering jobs in Pittsburgh, PA look for?

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Nvidia Engineering jobs near you
Infographic showing various Nvidia Engineering job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $142,582 per year, or $68.5 per hour.

Autonomy Engineer

Software Engineering Institute

Pittsburgh, PA • On-site

Full-time

This job post has expired 5 days ago. Applications are no longer accepted.

Job description

What We Do
At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of Artificial Intelligence (AI) technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.
As our government customers adopt AI and machine learning (ML) to provide leap-ahead mission capabilities, we:
  • build real-world, mission-scale AI capabilities through solving practical engineering problems.
  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities.
  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities.
  • identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape.

Are you creative, curious, and collaborative? Do you enjoy doing meaningful and complex work? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team today!
Position Summary:
As an autonomy engineer in the AI for Autonomy Lab, you will identify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs. The AI for Autonomy Lab researches and demonstrates the application of AI-related technologies for improving the performance of autonomy systems. This position will have a primary focus on enhancing our simulation capabilities and applying these tools to support autonomy-related projects.
Duties:
  • Solution Development: You'll work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.
  • Hands-on Prototyping: You'll conduct and lead novel prototyping in applied artificial intelligence with a focus on machine learning in autonomy and uncrewed systems (multi-domain).
  • Strategy: You'll work with AI Division leaders and colleagues to plan, develop, and carry out an overall research and engineering strategy, and to influence the national research and engineering agenda regarding future technology.
  • Collaboration: You'll actively participate on teams of software developers, researchers, designers, and technical leads. You'll build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research and engineering directions.
  • Mentoring: You'll contribute to improving the overall technical capabilities of the team by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI AI Division.

Requirements:
  • BS in Computer Science or related discipline with eight (8) years of experience; MS in the same fields with five (5) years of experience; PhD in Computer Science with two (2) years of experience.
  • This position is based onsite 5 days per week at SEI's offices in either Pittsburgh, PA or Arlington, VA.
  • Flexible to travel to other SEI offices in Pittsburgh and Washington, DC, sponsor sites, conferences, and offsite meetings on occasion. Moderate (25%) travel outside of your home location.
  • You will be subject to a background investigation and must be eligible to obtain and maintain a Department of War security clearance.

Knowledge, Skills, and Abilities:
  • Deep Technical Knowledge: You have performed extensive research or engineering activities in applied autonomy and artificial intelligence. You have worked with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas. In addition, you have demonstrated applying systems engineering principles and collaborated across multi-disciplinary project teams. You have supported multiple phases of the engineering lifecycle and understand the requirements for successful deployment and operation of complex systems.
  • Modeling & Simulation: You have deep experience using simulators for development, ML model training, and evaluation activities supporting uncrewed vehicle use cases. You understand current state of the art modelling techniques to build digital twin 3D objects and environments. You have addressed challenges related to marine, land, or space domains including sensor performance and collision meshes. Experience with physics-based simulators such as NVIDIA's Issac Sim is required.
  • Robotics & Autonomy: You have a strong understanding of robotics principles and design techniques for air, sea, or land-based vehicles. You have experience applying machine learning within these domains and understand the related implications and challenges. Your experience includes areas such as sensor fusion, navigation, object search/tracking, collision avoidance, multi-agent collaboration, and human-machine teaming.
  • Machine Learning: You have proven understanding of machine learning principles and have experience in applying machine learning techniques to real-world problems, showcasing a track record of successful implementations. You have designed and implemented complex machine learning functions and architectures tailored to specific autonomous systems. You are familiar with simulation environments and their role in training and testing machine learning models.
  • System Evaluation: You have designed and conducted system evaluation activities for ML components to assess operational fit and readiness. You have experience working with model experimentation software, such as MLFlow or Weights & Biases for rigorous model development and selection.
  • Applied Full-Stack Implementation: You have strong development experience and can design and implement software and systems resources for packaging and managing requirements for AI and ML prototypes. You frequently use tools like Docker to manage software resources and pipeline orchestration. You may have experience building applications in cloud platforms (Azure, AWS, Google Cloud Platform).
  • Communication and Collaboration: You have strong written and verbal communication skills and can interact collaboratively and diplomatically with customers and colleagues. You grasp the big picture, direction, and goals of an effort while focusing great attention to detail. You can present complex ideas to people who may not have a deep understanding of the subject area.
  • Dedication: You can meet deadlines while multi-tasking-sometimes under pressure and with shifting priorities.
  • Creativity and Innovation: You are creative and curious, and you are inspired by the prospect of collaborating with premier members of the technical staff and other visionaries at Carnegie Mellon and other universities and organizations. You quickly learn new procedures, techniques, and approaches. You are forward-looking and can connect research and engineering with practical challenges.
  • Knowledge and Learning: You possess broad technical interests along with a deep knowledge of a particular field such as machine learning, autonomy and adaptive systems, or data analytics.

Preferred Experience:
  • Thought Leadership and Publications: You have a track record of synthesizing lessons learned from research or engineering activities for publication. You have a reputation for the highest level of research and engineering integrity. You have demonstrated contributions and have published research, code (e.g., models, data, software applications), or technical perspectives.
  • Familiarity with Emerging Trends and Opportunities: You are familiar with technical challenges and emerging trends in computing and information science, and you are aware of opportunities in industry and government.
  • Technical Leadership: You have led technical projects and have experience collaborating across research teams and mentoring other researchers.
  • Proposals: You have formulated and delivered successful research and engineering proposals to funding agencies and led the resulting projects.
  • Government Projects: You have worked or are familiar with Navy, Marine, Air Force, Army, Space Force, DARPA, IARPA, Service Labs, or other government research sponsors.

Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

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