דרושים » תוכנה » Software Engineer - Drivers & Virtualization

As a Performance Software Engineer, you will be instrumental in building the core computation software that runs on custom AI accelerators. Your work will bridge the gap between host systems and proprietary hardware, encompassing everything from a custom on-board kernels to the sophisticated tooling required for real-time debugging. You will be a key player in chip bring-up and the long-term development of high-performance computation primitives and kernels, ensuring our architecture operates with maximum efficiency and deterministic performance.

Responsibilities
Develop and optimize low-level software primitives in C/C++, assembly, and architecture-specific intrinsics, primarily for RISC-V and ARM platforms.

Implement performance-critical kernels, runtime components, hardware abstraction layers, drivers, and firmware operating in bare-metal or highly constrained environments.

Work closely with hardware architects and RTL/design teams to define and validate hardware-software interfaces, memory maps, register interfaces, interrupts, synchronization mechanisms, and boot flows.

Analyze and optimize software for latency, throughput, memory footprint, instruction count, and efficient use of processor and accelerator features.

Bring up and debug software on simulation, emulation, FPGA, and silicon platforms, including low-level hardware/software integration issues.

Develop validation tests, benchmarks, and diagnostic tools for new processor, DSP, accelerator, and SoC functionality.

Contribute to architecture decisions around ISA extensions, compiler intrinsics, memory hierarchy, DMA, cache/coherency behavior, and software-visible hardware features.

We are looking for a Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need an individual contributor who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.

We are looking for an outstanding engineer to join our software architecture group and help shape the next generation of our networking products, SmartNICs, and DPUs. In this role, you will work closely with system architects, software/firmware engineers, hardware designers and product stakeholders to define component-level and system-level solutions for advanced datacenter platforms.

You will join a team working at the intersection of AI networking, virtualization, operating systems, security, management, and programmable acceleration. Our mission is to push the boundaries of modern datacenter infrastructure and help define the platforms of tomorrow.

What Youll Be Doing:

Work with architects and engineers to define software architecture for our networking devices, SmartNICs, and DPUs.

Analyze system requirements across networking protocols, virtualization, operating systems, security, management, and services.

Research new ideas, evaluate design alternatives, and build proof-of-concept models, simulations, and prototypes.

Collaborate with software, firmware, and hardware teams on HW/SW co-design, performance, scale, and resource-utilization challenges.

Learn complex datacenter technologies and turn them into clear architecture proposals, design documents, and technical presentations.

Were looking for engineers who are proactive, curious, and take full ownership of their work. In this role, youll have the opportunity to drive real impact, shape the direction of our product, and grow as a technical leader.

You will:
Take end-to-end ownership of features-from design and implementation to deployment and ongoing improvement.
Build high-quality, scalable, and resilient systems using modern engineering practices.
Work closely with PM, design, and security experts to define and deliver customer-facing experiences.
Drive technical direction and make thoughtful tradeoffs that balance speed, quality, and long-term maintainability.
Bring a strong sense of initiative-identifying opportunities, raising issues early, and pushing ideas forward.

The Networking Advanced Development Software team develops new groundbreaking technologies to enable new market shares for the company and tighten customer relationships. These are emerging technologies in networking and distributed computing for the booming AI factories and data centers. They span areas such as AI neural networks, Deep Learning, High Performance Computing (HPC), Storage, Cloud, SW Defined Network, Network Function Virtualization, 5G NR and more. We develop the solutions top-down, all the way from application behavioral analysis, to architecture definition and down to the implementation, using the world-leading our devices. The development traverses any needed component - application SW, middleware SW, OS kernel subsystems, device drivers, embedded SW (Firmware) and CUDA GPU. We collaborate with partners and key customers in the analysis processes and engage with open source communities introducing our leading features.

What youll be doing:

Lead a team of 5 engineers in the advanced technologies development.

Design and implement solutions throughout all layers from high level application, OS and driver subsystem to firmware.

Work on impactful projects involving state-of-the-art high-performance computing hardware and software.

Provide insight and technical guidance and collaborate with peers from across the company - including software architecture, chip architecture, and engineering departments to improve our future technology.

Collaborate with our partners and customers.

We are looking for an outstanding Senior Networking Software Architect to join the NIC/DPU Software and Firmware Architecture group. In this role, you will help define the next generation of our datacenter and AI networking platforms, with focus on DPU management, QoS, performance, telemetry, and software architecture across stacks. You will work closely with hardware designers, firmware/kernel driver teams, system engineers, validation, product management and customers. The role spans early architecture definition, pre-silicon design, bring-up, and production readiness for large-scale AI and cloud datacenter deployments.

What Youll Be Doing:

Own software and system architecture for next-generation DPU management, QoS, performance, telemetry, and observability features.

Define end-to-end control and management flows across DOCA, host drivers, embedded firmware, BMC, management controllers and external management systems.

Specify telemetry and observability requirements, including counters, logs, traces, events, health monitoring, debug data, and streaming telemetry.

Define management interfaces and APIs for configuration, provisioning, lifecycle operations, diagnostics, and field serviceability.

Write clear architecture specifications, interface definitions, flow diagrams, and design documents for software, firmware, and system teams.

Partner with R&D teams to translate high-level architecture into implementable designs and guide features through development, validation, silicon bring-up, and production.

Analyze system performance bottlenecks, interoperability issues, telemetry gaps, and customer-reported issues, then feed learnings into future architecture.

Collaborate with system and cluster architects to ensure NIC/DPU features fit end-to-end AI datacenter and cloud networking designs.

We are seeking a talented and experienced Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure. This role requires deep system-level architecture understanding, the ability to handle large-scale clusters processing petabytes of data, and mastery of modern C/C++ and Linux environment internals.
Key Responsibilities
Design & Develop Core Components: Build, maintain, and optimize highly scalable, resilient distributed services, storage engines, or data-processing pipelines written in C/C++.
System Architecture & Resilience: Drive architectural discussions and implementations around high availability, data consistency, replication mechanisms, fault tolerance, and multi-node concurrency.
Performance Optimization: Optimize hot execution paths, low-level data structures, memory management, and I/O subsystems to guarantee high throughput and minimal latency.
Complex Debugging & Troubleshooting: Investigate and resolve intricate production issues spanning the application layer, distributed networking protocols, file systems, and operating system kernels.
End-to-End Ownership: Take full technical ownership of critical features-from ambiguous requirements and system design through implementation, rollout, and observability in production environments.
Teams
Storage Platform: Focuses on building a next-generation distributed storage platform handling petabytes of data across large clusters specifically designed to power AI, enterprise, and analytics workloads. Handling everything that touches the hardware and operating system aspects in a software defined storage system
Data Path: Focuses on engineering a highly distributed, latency-critical Hot I/O Data Path and Element Store engine. This role is responsible for the ingestion, state-of-the-art compression, encoding, and retrieval of multi-protocol data (files and objects) under massive concurrency and ultra-low latency requirements.
Database: Focuses deeply on core relational database internals, specifically designing low-level storage engines, B-Tree/LSM-Tree data structures, MVCC concurrency control, and query execution planners.
Kernel: Focuses on the lowest software layers, emphasizing Linux Kernel development and block-level storage/file system engineering.
Protocols: Focuses strictly on engineering high-concurrency data/metadata paths that replicate external AWS S3 object-storage behavior and correctness under heavy retry and failover pressure.
Cloud: Focuses on cloud-native storage deployment, adapting and scaling complex high-availability storage infrastructure across major hyper-scaler cloud environments (AWS, Azure, GCP).
Compute Kafka: Focuses on distributed event-streaming and messaging platforms, specifically building a high-scale, exactly-once broker compatible with the Apache Kafka wire protocol.

The MLIL DataPlane team is looking for a Senior Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need a senior IC who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures (decoder-only, mixture-of-experts) end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.
- Mentor engineers, drive design reviews, and raise the engineering bar across the team.

The MLIL DataPlane team is looking for a Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need an individual contributor who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.

We are looking for an excellent Drivers Team leader to lead the Inbox Linux Drivers team and make a wide impact on the company products and teams worldwide. The role includes leading the development and maintenance of cutting-edge Linux kernel drivers and userspace libraries for our networking technologies, while managing a team of highly skilled Linux engineers responsible for delivering production-quality software across multiple products and distributions.

What youll be doing:

Lead a team of Linux kernel engineers responsible for developing, maintaining, and delivering Linux networking drivers for our NICs across multiple product lines, including Inbox drivers, our Kernel, and DOCA Host.

Drive the design, implementation, maintenance, and integration of Linux kernel drivers and accompanying userspace libraries for state-of-the-art Ethernet and RDMA networking technologies.

Own the teams technical execution, roadmap, prioritization, and delivery while mentoring engineers and fostering technical excellence.

Collaborate closely with architecture, firmware, hardware, validation, DevOps, product, and customer-facing teams across the globe to deliver robust and scalable networking solutions.

Lead complex debugging and performance investigations across the Linux networking stack, working with both internal stakeholders and open-source communities.

Ensure high software quality through strong engineering practices, code reviews, automation, and continuous integration.

Be part of an experienced organization with a collaborative culture, solving challenging problems that power next-generation AI, cloud, and high-performance computing infrastructure.