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As an ML Software Engineer with a focus on low-level and CUDA-based optimizations, you will play a key role in shaping the design, performance, and scalability of machine learning inference systems. Youll work on deeply technical challenges at the intersection of GPU acceleration, systems architecture, and ML deployment.
Your expertise in CUDA, C/C++, and performance tuning will be crucial in enhancing runtime efficiency across heterogeneous computing environments. Youll collaborate with designers, researchers, and backend engineers to build production-grade ML pipelines that are optimized for latency, throughput, and memory use, contributing directly to the infrastructure powering next-generation AI products.This role is ideal for an engineer with strong systems-level thinking, deep familiarity with GPU internals, and a passion for pushing the boundaries of performance and efficiency in machine learning infrastructure.

Responsibilities
Design and implement highly optimized GPU-accelerated ML inference systems using CUDA and low-level parallelism techniques
Optimize memory, compute, and data flow to meet real-time or high-throughput constraints
Improve the performance, reliability, and observability of our inference backend across diverse compute targets (CPU/GPU)
Collaborate with cross-functional teams (including researchers, developers, and designers) to deliver efficient and scalable inference solutions
Contribute to ComfyUI and internal infrastructure to improve the usability and performance of model execution flows
Investigate performance bottlenecks at all levels of the stack-from Python to kernel-level execution
Navigate and enhance a large, complex, production-grade codebase
Drive innovation in low-level system design to support future ML workloads

Required Experienced C++ Compiler Engineer for Deep Learning
We are the world leader in automotive and driving assistance systems, developing the world's most advanced software technologies and hardware architectures.
Our group is located in Haifa and is responsible for enabling the deep learning and computer vision algorithms on the platform. The technology we develop enables state-of-the-art deep neural networks to run efficiently in vehicles - contributing to saving lives and enabling autonomous vehicles.
This is an exciting opportunity to work with highly talented engineers and be a part of a product with a lot of innovation and work on cutting-edge compiler and optimization technologies in the AI domain.
What will your job look like?
Shape our product by applying cutting-edge deep learning network optimization techniques and will have the chance to influence future generations of our hardware and software
Develop a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow and PyTorch and converts them into code suitable for execution on custom-built hardware
Use state-of-the-art open-source technologies such as MLIR and work closely with the open-source community
Develop optimized implementations of a variety of neural-network operations and new optimization techniques and algorithms to efficiently map ML models onto our state-of-the-art systems
Develop a toolchain that will provide a quantum leap in Deep learning capabilities and performance.

Were looking for an IoT Embedded Linux engineer to design, build, and own the software stack that powers our edge devices in the field. Youll craft resilient Linux-based systems (from bootloader to application), ensure secure and reliable connectivity to the cloud, and work closely with hardware, manufacturing, and backend teams to deliver production-ready devices at scale.
A Day In Your Life :
Own the embedded Linux platform: BSP, kernel configuration, device tree, bootloaders (e.g., U-Boot), systemd services, and startup/upgrade flows.
Develop user-space applications using object-oriented principles (C++/Go/Rust/Similar) to implement core device logic and features, leveraging available libraries and frameworks.
Build production images using Yocto or Buildroot, manage layers/recipes, and maintain reproducible builds for multiple hardware variants.
Implement secure OTA updates (e.g., Mender, RAUC, SWUpdate), with A/B partitions, rollback, and signing-targeting zero‑touch fleet upgrades.
Harden devices for security: filesystem permissions, sandboxing (e.g., AppArmor/SELinux), secure boot/TPM, key management, CVE tracking, and update policies.
Deliver robust connectivity: Ethernet/Wi‑Fi/Cellular (LTE), BLE gateway roles, MQTT/HTTPS, VPN/WireGuard; optimize reliability, roaming, and reconnection logic.
Instrument and debug in the field: journald, core dumps, remote shell, metrics/health checks; trace with strace/perf/tcpdump and diagnose with Wireshark.
Collaborate across disciplines: work with HW, manufacturing, QA, backend, and product to define requirements, provisioning flows, and factory test automation.
Raise the bar on quality: CI/CD for cross‑compilation, unit/integration tests, static analysis, reproducible builds, and fleet-safe release practices.

We are a Software Embedded Development Engineer to design, develop, and optimize mission-critical embedded software for cloud infrastructure. You will join teams focused on networking, machine learning acceleration, and high-performance computing (HPC), impacting millions of our services globally.

Cutting-Edge Technology: Work on custom silicon (e.g., Graviton, ML accelerators) and innovative networking solutions at the intersection of hardware and software.

Growth & Innovation: Benefit from AWSs resources, mentorship programs, and opportunities to publish technical content.

We are looking for an outstanding software engineer for its software team.
Responsible for programming a component, feature and or feature set.
Works independently and contributes to the immediate team and to other teams across business.
You will also contribute to design discussions.
Job Description
Roles and Responsibilities:
Be responsible for defining, developing, and evolving software in a fast paced and agile development environment using the latest software development technologies and infrastructure
Drive increased efficiency across the team, eliminating duplication, leveraging product and technology reuse
Support process improvements which guide the development, sustaining & support activities
Engage subject matter experts in successful transfer of complex domain knowledge
Apply principles of SDLC and methodologies like Lean/Agile/XP, CI, Software and Product Security, Scalability, Documentation Practices, refactoring and Testing Techniques
Write code that meets standards and delivers desired functionality using the technology selected for the project
Understand performance parameters and assess application performance
Work on core data structures and algorithms and implement them using technology chosen
Proactively share information across the team, to the right audience with the appropriate level of detail and timeliness

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization 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 engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating in 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.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- 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 Team Lead, you will lead and mentor a backend development team working on a complex, large-scale medical imaging platform. This role combines Agile leadership with hands-on technical contribution, driving high-quality software delivery in a regulated, customer-focused environment.

Your role

You will act as the Agile facilitator and technical leader of a Radiology Informatics backend team within Image Management in Israel. You will guide the team in delivering scalable, high-performance software that supports advanced PACS solutions used by hospitals worldwide.
Serve as Scrum Master, ensuring effective adoption and continuous improvement of Agile (SAFe) practices
Lead team planning and execution toward iteration and program objectives
Contribute up to 50% hands-on software development and drive technical decision‑making.
Drive complex development efforts and resolve technical blockers
Promote clean, scalable, high-quality code and strong engineering standards
Ensure compliance with development processes, quality metrics, security, and regulatory requirements
Encourage system thinking, domain knowledge, and strong customer focus
Provide clear accountability, remove impediments, and act as an escalation point
Drive innovation through technical reviews, best practices, modern engineering approaches, and the adoption of AI development tools to enhance productivity and code quality
Collaborate with global cross-functional teams and stakeholders
Develop team capabilities through mentoring, delegation, and structured execution.

Required Senior Emulation Engineer, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of our platforms, we make our product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
Maintain and upgrade emulation models and infrastructure and act as a primary interface to emulation vendors.
Explore emulation methodologies, gather feedback from the team and customers, and implement emulation workflows and methodologies.
Create tooling and automation to support emulation Electronic design automation (EDA) tools, licensing, and job management in our infrastructure.
Support emulation team members with debugging hardware, tooling, and project-specific issues.
Help to bring up external interfaces (e.g., DDR, Peripheral Component Interconnect Express (PCIe), Ethernet, etc.) on the emulation platforms and create standalone test cases for tool issues encountered in the emulation compile and runtime flows.

Come join the Agentic AI science team in building the next generation models for intelligent automation.

We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.