דרושים Compiler Engineer - Gpu Debugging Tools ב-אנבידיה ב-פולין

What you’ll be doing:

• Research, prototype, develop and optimize solutions, tools and libraries for deep learning, data analytics, machine learning, or scientific computing

• Analyse, influence and improve deep learning libraries and frameworks standards and APIs according to good engineering practices

• Collaborate with team members and other partners

What we need to see:

• Excellent Python and C/C++ programming knowledge

• 8+ years of work experience in software development

• Experience in design and implementation of complex systems with decoupled dependencies

• Knowledge of design patterns and software engineering principles

• Strong analytical skill, knowledge about algorithms and data structures

• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects.

• Good communication and documentation habits

What you will be doing:

• Driving end-to-end responsibility for implementing and integrating major new features into the core storage solutions.

• Maintaining and improving the SPDK project (https://spdk.io/), serving the broader open-source storage community.

• Collaborating closely with hardware and other software teams to expose new, groundbreaking hardware capabilities.

• Implementing critical performance improvements and low-latency optimizations across the storage stack.

• Participating actively in the design and refinement of our next-generation technology storage solutions.

What we need to see:

• A degree in Computer Science, Software Engineering, or a related field (or equivalent experience).

• 8+ years of expertise as a C/C++ software engineer, with a strong emphasis on systems-level programming.

• Deep knowledge of Linux and Networking stack fundamentals.

• Demonstrated leadership skills; quickly adapting to new technical environments and providing clear technical guidance to peers.

• Proven familiarity with storage protocols (e.g., NVMe).

• A commitment to high-quality code through rigorous testing, code reviews, and robust design practices.

Ways to stand out from the crowd:

• Extensive experience with RDMA (Remote Direct Memory Access) and its application in low-latency systems.

• A deep understanding of SoC (System-on-a-Chip) hardware design and its influence on software performance.

• Serving as a core maintainer or significant contributor to a widely-used, high-visibility open-source project.

• Prior work with kernel bypass techniques and user-mode driver architectures.

What you’ll be doing:

• Design and implement high‑performance soft‑tissue simulation modules for Isaac for Healthcare, targeted at real‑time and near real‑time use cases.

• Develop and integrate SOTA algorithms spanning FEM and MPM variants; build on top of Newton, our newest physics simulation engine, and evaluate trade‑offs between accuracy, stability, and performance for surgical interactions (contact, friction, cutting/tearing, suturing, cautery, tool‑tissue coupling).

• Prototype and productize GPU‑accelerated kernels (e.g., with NVIDIA Warp; CUDA knowledge a plus) and optimized C++ backends with clean Python bindings for Isaac workflows.

• Prototype workflows with the latest deep-learning frameworks for Physics AI models in simulation environments (PhysicsNeMo).

• Integrate simulation components with Isaac Sim and Isaac Lab for closed‑loop robotics/RL training, data generation, and hardware‑in‑the‑loop evaluation.

• Collaborate with robotics, perception, and product teams to translate clinical/surgical requirements into simulation features and APIs.

• Build and contribute examples, docs, and tutorials; raise code quality via reviews, CI, and reproducible builds/releases.

• Mentor junior engineers and work with external partners (research labs, device makers) to validate models against experimental or clinical data.

What we need to see:

• Bachelor’s degree (or equivalent experience) in Computer Science, Robotics, Mechanical/ Biomedical Engineering, Applied Math, or related field.

• 7+ years building physics‑based simulation software or real‑time graphics/robotics systems.

• Strong proficiency in C++ and Python.

• Solid foundation in numerical methods, linear algebra, and continuum mechanics relevant to deformable bodies.

• Hands‑on experience delivering production‑quality features: profiling, debugging, testing, and shipping products that meet QA standards.

• Excellent collaboration and communication skills; ability to translate research prototypes into maintainable, documented components.

Ways to stand out from the crowd:

• Prior work with Isaac Sim and/or Isaac Lab (sensors, articulation, RL pipelines, USD/Omniverse workflows).

• Deep experience with FEM (e.g., corotational, nonlinear, solid mechanics) and/or MPM (e.g., MLS‑MPM/APIC) for soft tissue; familiarity with PBD/XPBD or hybrid schemes.

• Background with physics engines or frameworks (PhysX, SOFA, MuJoCo, Bullet, Taichi, etc.) anddifferentiable/learning‑in‑the‑loopsimulation.

• Familiarity with surgical robotics or medical imaging pipelines (e.g., mesh generation from DICOM/NIfTI, domain randomization for perception).

• Contributions to open‑source simulation/robotics projects, publications, or public GitHub repositories demonstrating mastery.

What you’ll be doing:

You will apply knowledge of compute programming models and compute architecture to build tools that provide actionable feedback to compute developers. You should be comfortable working in existing driver code and application code as well as writing new shared libraries and targeted performance tests, and have an eagerness to learn about new compute and graphics drivers, GPU architectures and operating systems.

• Develop the Compute Sanitizer (which is a suite of memory checker) tools for GPUs running on Linux, Windows, and embedded operating systems.

• Work with tools, compiler, architecture and driver teams to design, implement and verify new features in the Compute Sanitizer stack.

• Work closely with internal and external partners including other peer organizations within NVIDIA.

• Effectively estimate and prioritize tasks in order to create a realistic delivery schedule.

• Write fast, effective, maintainable, reliable and well-documented code.

• Provide peer reviews to other engineers, including feedback on performance, scalability and correctness.

• Document requirements and designs, and review documents with teams throughout NVIDIA.

• Mentor junior engineers.

What we need to see:

• BS or MS in Computer Science or equivalent experience

• 5+ years of experience

• Strong programming ability in C, C++, Assembly Language and scripting languages

• Excellent knowledge of computer architecture of x86 or ARM CPUs

• Strong problem solving and debugging skills

• Familiar with low-level programming using assembly languages

• Source control understanding (git, Perforce, etc.)

• Ability to self-manage, communicate, and adapt in a fast paced, high demand environment with changing priorities and direction

• Excellent communication skills, written and verbal

Ways to stand out from the crowd:

• CUDA/OpenCL knowledge

• Experience with code patching

• ELF/DWARF knowledge

We are looking for aSenior Deep Learning Engineerto help bring Cosmos World Foundation Models from research into efficient, production-grade systems. You’ll focus on optimizing and deploying models for high-performance inference on diverse GPU platforms. This role sits at the intersection of deep learning, systems, and GPU optimization - working closely with research scientists, software engineers, and hardware experts.

What you'll be doing:

• Improve inference speed for Cosmos WFMs on GPU platforms.

• Effectively carry out the production deployment of Cosmos WFMs.

• Profile and analyze deep learning workloads to identify and remove bottlenecks.

What we need to see:

• 5+ years of experience.

• MSc or PhD in CS, EE, or CSEE or equivalent experience.

• Strong background in Deep Learning.

• Strong programming skills in Python and PyTorch.

• Experience with inference optimization techniques (such as quantization) and inference optimization frameworks, one of: TensorRT, TensorRT-LLM, vLLM, SGLang.

Ways to stand out from the crowd:

• Familiarity with deploying Deep Learning models in production settings (e.g., Docker, Triton Inference Server).

• CUDA programming experience.

• Familiarity with diffusion models.

• Proven experience in analyzing, modeling, and tuning the performance of GPU workloads, both inference and training.

What you’ll be doing:

• Research, prototype, develop and optimize solutions, tools and libraries for deep learning, data analytics, machine learning, or scientific computing

• Analyse, influence and improve deep learning libraries and frameworks standards and APIs according to good engineering practices

• Collaborate with team members and other partners

What we need to see:

• Excellent Python and C/C++ programming knowledge

• 8+ years of work experience in software development

• Experience in design and implementation of sophisticated systems with decoupled dependencies

• Knowledge of design patterns and software engineering principles

• Strong analytical skill, knowledge about algorithms and data structures

• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects

• Good communication and documentation habits

What you will be doing:

• Running a lot of builds and tests on a lot of architectures, operating systems, and devices.

• Collecting a lot of data and working collaboratively to brainstorm and build infrastructure and tools to make sense of it all.

• Building relationships that allow us to work together as a team, not a group.

• Working in a highly dynamic environment where we have to think on our feet.

What we need to see:

• 6+ years of relevant industry experience.

• Proficient with Linux.

• Bachelors degree in a related area of study or equivalent experience.

• Expert with scripting in one or more of Python, Perl, shell, Groovy, etc..

• Strong background with deploying, configuring, and debugging distributed systems.

• You should be familiar with the software build process (read compiling C++ code with GNU Make, CMake, Visual Studio, MSBuild, etc.).

• Background with some form of source control management (SCM), preferably git.

• Familiar with containers.

Ways to stand out from the crowd:

• Experience with HPC hardware systems such as compute clusters and HPC software performance benchmarking on such systems.

• System administrator level experience with multi-user Linux servers.

• Background with GPU accelerated systems.

• Experience working in an environment where Agile processes and methodologies are used.