Role Overview

Astera Labs is establishing a strategic R&D center in Israel to drive the development of complex semiconductor chips that solve the critical 'data bottlenecks' enabling the future of AI at scale. As we expand our presence in Israel, we're seeking a visionary Design Verification Student to help build our local engineering powerhouse from the ground up. This is a unique opportunity to take on meaningful product ownership in a new site, designing complex solutions that sit at the heart of our most ambitious connectivity projects.

As a Design Verification Student, you will be at the forefront of quality, learning how to ensure that the chips powering the world's largest AI clusters are bug-free and robust.
This isn't just about running tests - it’s an opportunity to learn advanced verification methodologies (UVM/SystemVerilog) alongside world-class engineers. You will support the development of sophisticated testbenches and help verify high-performance digital blocks that sit at the heart of AI infrastructure.

Key Responsibilities

• Assist in building and maintaining System Verilog/UVM-based testbenches, including monitors, checkers, and functional coverage models
• Run simulations, analyze failures, and work with the design team to debug and resolve RTL issues
• Help define and implement functional coverage and assertions to ensure all "corner cases" of the design are tested
• Utilize and improve scripting (Python/Tcl) to streamline verification flows and result reporting
• Partner with Design Engineers to understand block specifications and ensure the verification plan matches the design intent

Basic Qualifications

• Pursuing a Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related technical field
• Ability to work at least 2 days a week at our Haifa/Tel Aviv center
• Strong understanding of Digital Logic and at least one programming language (C/C++ or Python)
• Basic familiarity with Verilog or SystemVerilog from academic projects or lab work
• A natural curiosity for "breaking things" and finding bugs, with a strong attention to detail
• Fluent in Hebrew and English with the ability to work effectively in a team environment

Preferred Qualifications

• Completed courses in VLSI, Digital Systems, or Computer Architecture
• Proficiency in Python, Perl, or Tcl
• Any prior exposure to UVM/OVM or constrained-random verification is a major plus
• Basic understanding of protocols like PCIe, Ethernet, or DDR

Lightricks is an AI-first company creating next-generation content creation technology for businesses, enterprises, and studios with a mission to bridge the gap between imagination and creation. At our core is LTX-2, an open-source generative video model, built to deliver expressive, high-fidelity video at unmatched speed. It powers both our own products and a growing ecosystem of partners through API integration.

The company is also known globally for pioneering consumer creativity through products like Facetune, one of the world’s most recognized creative brands, which helped introduce AI-powered visual expression to hundreds of millions of users worldwide. We combine deep research, user-first design, and end-to-end execution from concept to final render, to bring the future of expression to all.

Why Join Us

We’re here to push the boundaries of what’s possible with AI and video - not for the buzz, but for the craft, the challenge, and the chance to make something genuinely new.

We believe in an environment where people are encouraged to think, create and explore. Real impact happens when people are empowered to experiment, evolve, and elevate together.

At Lightricks, every breakthrough starts with great people and a collaborative mindset. If you're looking for a place that combines deep tech, creative energy, and zero buzzword culture, you might be in the right place.

What you will be doing

 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 Lightricks’ machine learning inference systems. You’ll 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. You’ll 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 Lightricks' 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

Your Skills and Experience

• 5+ years of experience in high-performance software engineering
• Advanced proficiency in CUDA, C/C++, and Python, especially in production environments
• Deep understanding of GPU architecture, memory hierarchies, and optimization techniques
• Proven track record of optimizing compute-intensive systems
• Strong system architecture fundamentals, especially around performance, concurrency, and parallelism
• Ability to independently lead deep technical investigations and deliver clean, maintainable solutions
• Collaborative and team-oriented mindset, with experience working across functional teams

Preferred Requirements

• Experience with low-level profiling and debugging tools (e.g., Nsight, perf, gdb, VTune)
• Familiarity with machine learning frameworks (e.g., PyTorch, TensorRT, ONNX Runtime)
• Contributions to performance-critical open-source or ML infrastructure projects
• Experience with cloud infrastructure and GPU scheduling at scale

Who we are

Lightricks is an AI-first company with a mission to bridge the gap between imagination and creation. At our core is LTX-2, an open-source generative video model, built to deliver expressive, high-fidelity video at unmatched speed. It powers both our own products and a growing ecosystem of partners through api integration.

Our flagship products include Facetune and LTX Studio, used by hundreds of millions of users worldwide. We combine deep research, user-first design, and end-to-end execution to bring the future of expression to all.

What you will be doing

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 Lightricks’ machine learning inference systems. You’ll 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. You’ll 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 Lightricks' 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 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

Your Skills and Experience

• 5+ years of experience in high-performance software engineering
• Advanced proficiency in CUDA, C/C++, and Python, especially in production environments
• Deep understanding of GPU architecture, memory hierarchies, and optimization techniques
• Proven track record of optimizing compute-intensive systems
• Strong system architecture fundamentals, especially around performance, concurrency, and parallelism
• Ability to independently lead deep technical investigations and deliver clean, maintainable solutions
• Collaborative and team-oriented mindset, with experience working across functional teams

Preferred Requirements

• Experience with low-level profiling and debugging tools (e.g., Nsight, perf, gdb, VTune)
• Familiarity with machine learning frameworks (e.g., PyTorch, TensorRT, ONNX Runtime)
• Contributions to performance-critical open-source or ML infrastructure projects
• Experience with cloud infrastructure and GPU scheduling at scale

Why Join Us

We’re here to push the boundaries of what’s possible with AI and video - not for the buzz, but for the craft, the challenge, and the chance to make something genuinely new.
We believe in an environment where people are encouraged to think, create, and explore. Real impact happens when people are empowered to experiment, evolve, and elevate together. At Lightricks, every breakthrough starts with great people and a collaborative mindset. If you're looking for a place that combines deep tech, creative energy, and zero buzzword culture, you might be in the right place.

We got you covered: 

• We run daily door-to-door shuttles, offering Car-to-go subscriptions for several locations in central Israel, plus free parking and train-station pickups.
• We’re proud to have 2 chef-led restaurants on site by the legendary Machneyuda Group (yes, that Machneyuda!), plus a bakery nestled in the heart of our office, filled daily with the scent of fresh pastries.
• We empower employees with cutting-edge tools and learning opportunities to grow and succeed through workshops, access and training on platforms, subscriptions, and clear guidelines for responsible AI use.

We’re looking for an IoT Embedded Linux engineer to design, build, and own the software stack that powers our edge devices in the field. You’ll 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.

What you bring

• 3–5 years of Embedded Linux experience shipping devices to production at scale.

• Strong proficiency in object-oriented programming (OOP) principles and multi-threading experience, with hands-on skills in C/C++/GO/Rust/Similar in user space (some kernel familiarity) and scripting (Bash, Python); expertise with build systems (CMake/Make, BitBake).
• Hands-on with Buildroot or Yocto Project (preferably Buildroot), including custom layers, recipes, and SDKs.
• Solid understanding of Linux kernel basics, device trees, drivers/BSP integration, bootloaders (U‑Boot), and systemd service design.
• Networking fundamentals: TCP/IP, DHCP/DNS, TLS, MQTT/HTTPS, VPN; experience with Wi‑Fi/cellular modules and AT command stacks is a plus.
• Proven experience with OTA frameworks, partitioning strategies, and rollback-safe update flows.
• Git fluency and experience with CI (GitHub Actions, GitLab CI or similar) for cross builds and test automation.
• BSc in EE/CE/CS (or equivalent practical experience).

Nice to have

• Device security: secure boot, TPM, disk encryption, SBOM/CVE remediation workflows.
• Real-time and performance: PREEMPT_RT, scheduling, latency tuning, power management.
• Edge packaging: containers (Docker/Podman) on ARM, OCI/CRUN, rootless strategies.
• Cloud & IoT: AWS IoT/Azure IoT, device identity/provisioning, fleet management tooling.
• Language breadth: Go or Rust for system services; protobuf/gRPC.
• Manufacturing flows: factory provisioning, E2E traceability, and end-of-line testing.

Perks

• Stock options
• Paid parental leave
• Flex PTO