דרושים » תוכנה » Senior Software Engineer- ML Network Stack, ML Network Stack

We are seeking an experienced engineer to join our team that owns the network stack for EC2 distributed AI/ML systems. The team develops support for a variety of frameworks and communication libraries including NCCL, NVSHMEM, NIXL, NCCL GIN, and Perplexity kernels. Solid knowledge of Linux, networking, and performant coding is important. Experience with embedded systems is valued, and experience with high-speed networking or HPC/RDMA interconnects is highly valued.

If you like solving hard problems, want to work with HPC and ML customers, iterate fast and deliver meaningful solutions at scale, then come join us! This truly is a role at the forefront of AI/ML-you'll be working on features for the largest clusters, with the largest customers, for the largest AI models.

Key job responsibilities
Be a senior engineer on a team that builds and maintains the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale. Use our internal CI/CD tools, Linux, and public AWS products to automate the delivery of our software to customers, saving developer time. Write Python code that effortlessly spools up large clusters and runs benchmarks and applications for ML and HPC workloads. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and create dashboards for developers and stakeholders. Invent automatic mechanisms to alert developers to functional and performance regressions so they never reach reach customers. Manage the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, cutting-edge releases and make it easy to evolve.

As a Sr. Software Engineer in our NoSQL and in-memory computing platform team, you will lead the software development of large-scale, distributed in-memory storage platform with sub-millisecond latency. You will leverage open source technologies like Valkey, Memcached, and our proprietary technologies. This includes data plane extremely fast and high throughput development, low level optimizations, asynchronous messaging, event-based technologies, real-time failure detection system, horizontal and vertical scaling, auto-remediation, high availability, fault tolerance, storage technologies, snapshoting, and disaster recovery.

In this role, you will have oversight of all things technical, own significant portions of the product, and serve as a mentor for other engineers in their areas of work. As the key member of the engineering team, you will have a significant influence on our overall strategy by helping define the product features, drive system architecture, and spearhead best practices. You will work to enable a quality product and set the groundwork for success in the next phase of the product and beyond. A commitment to teamwork, hustle, and strong communication skills (to both business and technical partners) are absolute requirements. Creating a reliable, scalable, and high-performance service requires exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience building large-scale distributed systems. You should be someone who enjoys working on complex system software, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals.

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 are looking for an 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.

You'll design and build features that shape how hundreds of millions of customers discover products. The problems here are genuinely novel - we're defining how LLMs integrate into real-time recommendation experiences, not applying established playbooks. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This team values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence, not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating for engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate features for a personalized recommendation system used by multiple teams and operating at our scale.
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

Required Staff Software Engineer, Cloud Storage, AI/ML
Tel Aviv, Israel
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of the Cloud Storages, your mission is to provide the most trusted planet-scale storage system, with reliability, efficiency, performance, and simplicity.
As a part of the Storage AI/ML Solutions team, you will be dedicated to exploring, architecting and developing next-generation storage solutions for the AI/ML ecosystem. You will bridge the gap between core storage infrastructure and the evolving demands of AI/ML workloads, from large-scale training to high-performance inference. You will deliver innovative solutions and sharing performance insights through benchmarks, enable customers to achieve optimal results and solidify Cloud Platform (GCP's) position as the premier platform for AI/ML.Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Design and implement high-complexity features, deliver production-ready code for storage solutions that address the specific demands of AI/ML workloads.
Architect scalable and performant storage solutions, apply data-driven decisions to optimize system efficiency and reliability.
Diagnose and resolve performance bottlenecks and intricate system issues, develop innovative, practical solutions to technical issues that arise at the intersection of storage and ML.
Collaborate with product and engineering stakeholders to translate customer requirements into technical specifications, ensuring the incubations output aligns with broader Cloud goals.

We are looking for Senior Software Engineer to join the Cumulus Linux team! We present you with an opportunity to be part of the team that develops the Network Operating System that powers data centers that are accelerated, disaggregated and software-defined to meet the exploding growth in AI and high-performance computing. You'll be part of a software development team responsible for defining and implementing core platform services, as well as Reliability, Availability and Serviceability features for Cumulus Linux, the Debian-based operating system for NVIDIA's market-leading Ethernet switches.

What you'll be doing:

Design and develop software for Cumulus Linux operating system (OS) which runs on our portfolio of data center switches.

Work on bringing up Cumulus Linux on next generation Nvidia switches.

Develop and maintain software in Python, C and Shell for our OS.

Collaborate with product, architecture, and engineering teams to deliver features on Cumulus Linuxs roadmap.

Debug and resolve issues reported by test and customer-facing teams.

Work with open source software that is part of our OS and fix issues as and when they are raised.

As a Backend Software Engineering, your job responsibilities will include:
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.
Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.
Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.
Make design decisions on the basis of performance, scalability, and future expansion.
Work in a Hybrid Engineering model and contribute to all phases of SDLC including design, implementation, code reviews, automation, and testing of the features.
Build efficient components/algorithms on a microservice multi-tenant SaaS cloud environment
Code review, mentoring junior engineers, and providing technical guidance to the team (depending on the seniority level).

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools:Utilize platforms such asGemini, Claude, and Cursorfor tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows:Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards:While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents:Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

Our team focuses on developing products to allow for personalizing the customers experience and providing them with real-time insights and revolutionary experiences using Computer Vision (CV) and Machine Learning (ML). You will get a chance to work on greenfield and large-scale engineering and science projects.

Key job responsibilities
- Own architecture and feature development for our Personalization and CV/ML teams.
- Partner with other engineers to ideate, design, and build scalable solutions.
- Utilize data science and ML to develop products that deliver great experiences for customers.
- Tackle complex technical challenges across the stack - from data pipelines to large scale services.