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You will work directly with founders, engineering leaders, and developer communities buildingThis role is ideal for someone who enjoyshands-on technical engagement, ecosystem building, and communicating complex technology in a clear and compelling way.
You will be a, shaping solution strategy, enabling partners, and helping drive the next generation of AI-powered retail innovation.
Serve as the trusted technical advisor, and champion for the developer ecosystem in Retail Industry, with multi-functional partners to drive adoption of NVIDIA technologies.
Help developers leverage NVIDIA’s tools for GenAI and LLMs- including Triton Inference Server, TensorRT-LLM, NeMo Framework, and CUDA-accelerated pipelines —to optimize model performance and scalability.
Build and deliver sample applications, tutorials, and technical content that highlight best practices for building with LLMs and agentic workflows.
Partner with solution architects to benchmark improvements and support performance tuning of LLM deployments across NVIDIA platforms.
Guide startups through integration with NVIDIA’s Gen AI stack and support their certification in NVIDIA partner programs.
Represent the company at industry events, developer meetups, andhackathons—evangelizingour LLM and Agentic AI strategy to a technical audience.
Gather developer feedback to inform product and roadmap decisions related to LLM inference, training, and deployment tooling.
Identify promising Gen AI startups and help them go to market through co-branded solution development and strategic partnerships
BS or Masters in Computer Science, Engineering, or equivalent practical experience.
8+ years in Developer Relations, AI engineering, startup GTM roles, or Technical Alliances.
Deep hands-on experience with LLMs (e.g., Qwen, Deepseek, LangChain, RAG pipelines) and autonomous agent frameworks.
Proficiency with Python, containerization tools (Docker, Kubernetes), and Linux-based development environments.
Understanding of model fine-tuning, prompt engineering, memory architectures, tool use in agent systems, and orchestration frameworks.
Excellent communication and storytelling skills—comfortable presenting to technical and business audiences.
Experience in retail AI, Machine Learning and Deep Learning applications
Familiarity with advanced computing, AI, and/or GPU acceleration platforms (Triton Inference Server, TensorRT-LLM, NeMo Framework, and CUDA-accelerated pipelines).
Successful history of building and scaling developer communities and delivering impactful technical enablement programs.
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What You’ll Be Doing:
Conduct in-depth analysis of customers' latest needs and co-develop accelerated computing solutions with key customers.
Assist in supporting industry accounts and drivingresearch/influencing/newbusiness in those accounts.
Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.
Understand and analyze customers' workloads and demands for accelerated computing, including but not limited to: LLM training/inference acceleration and optimization, application optimization for Agent AI/RAG, kernel analysis, etc.
Assist customers in onboarding NVIDIA's software and hardware products and solutions, including but not limited to: CUDA, TensorRT-LLM,NeMoFramework, etc.
Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications.
Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community.
What We Need To See:
3+ years’ experience withresearch/development/applicationof Machine Learning, data analytics, or computer vision work flows.
Outstanding verbal and written communication skills
Ability to work independently with minimal day-to-day direction
Knowledge of industry application hotspots and trends in AI and large models.
Familiarity with large model-related technology stacks and common inference/training optimization methods.C/C++/Python programming experience
Desire to be involved in multiple diverse and innovative projects
Experience using scale-out cloud and/or HPC architectures for parallel programming
MS or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, Neuroscience, Experimental Psychology or equivalent experience.
Ways To Stand Out From The Crowd:
AIGC/LLM/NLP experience
CUDA optimization experience.
Experience with Deep Learning frameworks and tools.
Engineering experience in areas such as model acceleration and kernel optimization.
Extensive experience designing and deploying large scale HPC and enterprise computing systems.
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What you will be doing:
Investigate and resolve sensor calibration and egomotion algorithm/toolchain issues across multiple OEM vehicle platforms.
Develop core autonomous driving functionality for global markets by fusing state-of-the-art perception DNNs with map signals.
Build real-time 3D world models for planning, integrating diverse inputs from sensors and external sources.
Develop and optimize LLM, VLM, and VLA systems for autonomous driving applications, including pre-training and fine-tuning.
Design innovative data generation and collection strategies to improve dataset diversity and quality.
Collaborate with cross-functional teams to deploy end-to-end AI models in production, ensuring performance, safety, and reliability standards are met.
What we need to see:
A MS, or PhD, or equivalent professional experience in Computer Science, Computer Engineering, Mathematics, Physics, or a related discipline.
Over 3 years of relevant industry experience.
Expertise in C/C++ programming, with a comprehensive understanding of standard C++ features, algorithms, and data structures, along with proficiency in Linux environments.
In-depth knowledge of parameter models for sensor calibration.
A solid grasp of digital image processing, three-dimensional multi-view geometry, nonlinear optimization, and KF/EKF.
A robust mathematical foundation, especially in matrix-related concepts.
Engineering expertise in developing and delivering deep learning applications for autonomous vehicles or robotics
Engineering expertise in developing and delivering real-time 3D world models for planning in AV system.
Excellent collaboration skills and the ability to work effectively with individuals from various nationalities and locations.
Ways to stand out from the crowd:
Experience with a range of sensors and their data (camera, lidar, radar, IMU, GNSS, CAN Odometry).
Extensive experience in SLAM algorithms
Extensive deep learning experience related to autonomous driving.
A track record of designing SLAM algorithms for successful ADAS projects.
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What you’ll be doing:
Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability
Experience designing, developing, and deploying AI agents to automate software development workflows and processes.
Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR).
Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.
Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.
What we need to see:
BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience.
Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent development
Strong background in implementing AI solutions to solve real-world software engineering problems.
Hands-on experience on Python/Java/Go with extensive python scripting experience.
Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch.
Full-stack, end-to-end development expertise, with proficiency in building and integrating solutions from the front-end (e.g., React, Angular) to the back-end (Python, Go, Java) and managing data infrastructure (SQL/NoSQL).
Experience with tools for CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools.
Good understanding of distributed systems, understanding of microservice architecture and REST APIs.
Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams.
Ways to stand out from the crowd:
Proven expertise in applied AI, particularly using Retrieval-Augmented Generation (RAG) and fine-tuning LLMs on enterprise data to solve complex software engineering challenges.
Experience delivering large-scale, service-oriented software projects under real-time constraints, demonstrating an understanding of the complex development environments this role will optimize.
Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data.
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What you’ll be doing:
Resolve complex escalations and technical issues by conducting meticulous research, reproducing problems, and performing in-depth troubleshooting for customers who are installing NVIDIA product and employment NVIDIA solutions.
Respond promptly to customer inquiries regarding product support via telephone, email, or conference calls.
Address customer issues that arise during installation, operation, maintenance, product application, or when dealing with interoperability matters with other vendors.
Actively participate in cross-functional team meetings and offer valuable feedback to the Engineering and Marketing departments regarding product requirements, customer experience, and support tools.
As a technical expert, develop, redefine, and document best practices to share with internal teams (Support and R&D) for the enhancement of support processes.
Conduct site visits and engage in conference calls with customers as needed.
What we need to see:
BS, MS, or PhD. or equivalent. Strong academic background in Computer or Electrical Engineering, Computer Science, or related degree.
Computing system knowledge.
6+ years of work-related experience in high speed signal, system build, network or GPU.
Strong expertise in python and Linux.
Familiar with hardware develop tools, scope and testing of signal integrity.
Excellent communication and planning skills, while being self-motivated with a focus on execution and quality
Ways to stand out from the crowd:
Strong background and project experience in server and NIC design.
Experts on signal integrity and optical modules.
System designer and architect from CSP, OEM and ODM, or application engineering background from semiconductor companies.
Willing to share.
Knowledge in NVIDIA platform.
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What you'll be doing:
Design and implement triggering systems and deploy containerized orchestration pipelines for distributed map creation, maintenance, and evaluation from crowdsourced vehicle data
Develop map quality detection systems including automated hotspot detection algorithms and human-in-the-loop review workflows for large scale map validation
Develop Python, C++, and JavaScript tools for map management, data validation, on-vehicle testing, and web-based geospatial visualizations
Build C++ modules for on-vehicle map integration with perception, localization, and other consumers to ensure end-to-end validation of the maps' impact on driving performance
Work with embedded systems and real-time constraints to optimize map consumption by autonomous driving software
Collaborate with perception, planning, and operations teams to improve map quality and real-time driving performance
What we need to see:
BS or MS degree in Computer Science, Software Engineering, or related field (or equivalent experience)
5+ years of proven experience building production data pipelines, distributed systems, mapping infrastructure, or map to vehicle integration
Strong C++ programming skills for performance-critical algorithms, data processing tools, and on-vehicle software
Strong Python programming skills for automation, workflow orchestration, and API development
Proficiency with JavaScript for building web-based tools, visualizations, and internal dashboards
Hands-on experience with Airflow or similar workflow orchestration frameworks
Experience with Docker, Kubernetes, and cloud platforms
Experience with Protocol Buffers, gRPC, and REST API design
Excellent problem-solving skills and ability to debug sophisticated distributed and embedded systems
Ways to stand out from the crowd:
Extensive experience with SD & HD mapping and autonomous vehicle software architectures
Deep understanding of how maps are consumed by localization, perception, and planning systems in autonomous vehicles
Deep knowledge of road topology generation, analysis, and graph partitioning algorithms
Experience with computer vision concepts pipelines (3D geometry, point clouds,structure-from-motion,COLMAP, SfM, visual odometry)
Experience debugging and profiling performance on embedded platforms (NVIDIA Orin, Xavier, etc.)
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What you’ll be doing:
Drive NVIDIA revenue in large auto accounts
Engage with various NVIDIA technology partners and identify areas of collaboration. Identify complementary technologies needed to build complex solutions using our computing platforms.
Create go-to-market execution w/ cross functional teams
Prioritize and report on key business metrics to measure and guide global industry teams.
Influence and align with sales and customer teams to understand customer requirements and build a scale out plan for target market technologies
Generating technology trends and market analysis
Represent and evangelize NVIDIA solutions at key industry events
What we need to see:
BS/MS (or equivalent experience) with 10+ years of BD/Sales experience in enterprise, especially AUTO industry
MBA/MS or advanced degree desired
Fluent English in speaking, reading, and writing
Experience in AI in autonomous driving is a plus
Strong leadership skills, self-starter
Excellent communication abilities and shared attitude
Ways to stand out from the crowd
Experience in successfully leading to build strategic partnerships and a versatile ISV ecosystem in Autonomous driving
Experience with deep learning and/or other AI technologies
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You will work directly with founders, engineering leaders, and developer communities buildingThis role is ideal for someone who enjoyshands-on technical engagement, ecosystem building, and communicating complex technology in a clear and compelling way.
You will be a, shaping solution strategy, enabling partners, and helping drive the next generation of AI-powered retail innovation.
Serve as the trusted technical advisor, and champion for the developer ecosystem in Retail Industry, with multi-functional partners to drive adoption of NVIDIA technologies.
Help developers leverage NVIDIA’s tools for GenAI and LLMs- including Triton Inference Server, TensorRT-LLM, NeMo Framework, and CUDA-accelerated pipelines —to optimize model performance and scalability.
Build and deliver sample applications, tutorials, and technical content that highlight best practices for building with LLMs and agentic workflows.
Partner with solution architects to benchmark improvements and support performance tuning of LLM deployments across NVIDIA platforms.
Guide startups through integration with NVIDIA’s Gen AI stack and support their certification in NVIDIA partner programs.
Represent the company at industry events, developer meetups, andhackathons—evangelizingour LLM and Agentic AI strategy to a technical audience.
Gather developer feedback to inform product and roadmap decisions related to LLM inference, training, and deployment tooling.
Identify promising Gen AI startups and help them go to market through co-branded solution development and strategic partnerships
BS or Masters in Computer Science, Engineering, or equivalent practical experience.
8+ years in Developer Relations, AI engineering, startup GTM roles, or Technical Alliances.
Deep hands-on experience with LLMs (e.g., Qwen, Deepseek, LangChain, RAG pipelines) and autonomous agent frameworks.
Proficiency with Python, containerization tools (Docker, Kubernetes), and Linux-based development environments.
Understanding of model fine-tuning, prompt engineering, memory architectures, tool use in agent systems, and orchestration frameworks.
Excellent communication and storytelling skills—comfortable presenting to technical and business audiences.
Experience in retail AI, Machine Learning and Deep Learning applications
Familiarity with advanced computing, AI, and/or GPU acceleration platforms (Triton Inference Server, TensorRT-LLM, NeMo Framework, and CUDA-accelerated pipelines).
Successful history of building and scaling developer communities and delivering impactful technical enablement programs.
These jobs might be a good fit