דרושים » תוכנה » senior guidance engineer

We are hiring a Senior Robotics Software Engineer to build the system the autonomy runs inside. You own the runtime - ROS2 architecture, module lifecycle, orchestration, state management, configuration, fault handling, and both ends of the stack: World Model ingestion and the Vehicle Interface down to the platform control systems.

You will face hard real-time constraints, embedded compute, and a system that has to keep behaving correctly when parts of it do not. You own the stack across its full depth, from the interfaces at its edges to how the whole thing behaves in the water.

What Will You Do?
Own the autonomy runtime: ROS2 and modern C++ architecture, module lifecycle, orchestration, state management, data flow, configuration, fault handling and recovery
Implement the system's two contracts: World Model ingestion and Vehicle Interface adapters to the platform control systems
Own deployment to the vessel compute: builds, packaging, versioning, configuration management and CI
Work with system engineering and field teams on vessel bring-up, sea trials and debugging in the field
Build logging, recording, replay and observability - the ability to take any run at sea and reproduce it exactly on a desk
Integrate and operate the simulation environment (SIL)
Own reliability, timing and performance of the stack on embedded hardware

We are hiring a Principal Autonomy Engineer to architect and lead the autonomous navigation stack of our unmanned surface vessel. You will own the architecture end to end - World Model, planning, decision making, vehicle interface, and you will decide how the brain itself is built: module decomposition, behavior architecture, arbitration, state ownership, and the core technology choices behind them. You will define technical requirements and reference scenarios, own the safety and degradation architecture, and hold the interfaces between autonomy, perception, the vessel platform and the field teams.

This is not an architecture role away from the code, but it is a leadership role. You will set the technical direction of the group and you will write the parts that matter most yourself - hands on principal.

What Will You Do?
Own the end-to-end architecture of the autonomous navigation stack: World Model - Planning - Decision Making - Vehicle Interface.
Define and own the World Model Contract: representation, uncertainty, timing and synchronization, coordinate frames, confidence and degradation modes.
Define and own the Vehicle Interface Contract: command semantics, platform guarantees, latency and failure behavior, and the abstraction that keeps the stack portable across platforms.
Decide how the autonomy brain is structured - module decomposition, behavior architecture, arbitration between behaviors, state ownership, data flow.
Design the safety and fail-safe architecture: degradation ladder, safe-state transitions, operator intervention, fault containment.
Stay hands-on in planning and decision-making code where the hardest problems are.
Lead technical hiring and technical direction for the autonomy group as it grows.

we are a global leader in advanced human-guided autonomous drone systems, and we are looking for a backend team lead to join our r&d organization and lead the development of the core software powering our Real-Time autonomous and mission-critical systems used by defense and security forces worldwide.
in this role, you will combine hands-on technical leadership with people management, guiding a team of backend developers while actively contributing to the design and implementation of high-performance C ++ systems. you will play a central role in shaping the technical direction of backend development, ensuring scalability, robustness, and production-readiness of mission-critical systems operating in real-world environments.
this is a unique opportunity to lead and influence development at the intersection of robotics, autonomy, and high-performance software engineering.
responsibilities:
lead, mentor, and grow a team of backend developers, fostering ownership, accountability, and technical excellence.
take full ownership of backend delivery, from design through production deployment.
act as a hands-on contributor to high-performance C ++ development in Real-Time and mission-critical environments.
collaborate closely with diverse (software and hardware) teams across the entire company to deliver integrated solutions.
ensure high performance, reliability, and efficient resource utilization in production systems.
conduct code and design reviews, enforce best practices, and maintain high development standards.
manage sprint planning, task prioritization, technical roadmap alignment, and delivery timelines within an agile framework.
support recruitment, onboarding, and professional development of backend engineers.

We are seeking a hands-on Applied AI Scientist to join our core R&D team and drive the development of next-generation AI systems for autonomous driving. This role sits at the intersection of applied research and deployment - you will go from reading papers to shipping production systems. You will work directly on our multi-layered autonomy architecture, with a primary focus on real-time predictive models for driving decisions.
A deep technical role for someone who thrives on turning cutting-edge research into real, working systems under hard constraints.
Responsibilities:
Own the research-to-deployment cycle for predictive driving models - from literature review and prototyping through to production integration
Design, implement, and iterate on real-time predictive models, including vision-language models, motion prediction models, and inverse reinforcement learning approaches (e.g., imitation learning, reward recovery)
Collaborate on higher-level reasoning systems, contributing to vision-language-action models that handle complex edge cases and long-horizon planning
Bridge cloud-scale training with edge deployment - work on model compression, quantization, speculative decoding, and efficient inference for embedded automotive platforms
Evaluate and integrate state-of-the-art techniques from the broader AI research community into our autonomy stack
Collaborate closely with internal R&D teams to unblock technical challenges, accelerate delivery, and raise the overall technical bar

We are looking for some exceptional talent to join our Design and Engineering team as a System Platform Team Lead
Your Day to Day.:
Lead a multidisciplinary team of embedded SW, FPGA/logic, verification and software engineers
Own the system-level architecture and execution of various SoC-based camera processing and control platforms including Xilinx MPSoC
Oversee development across ARM A53/R5, Linux, bare metal, FPGA logic, HLS, micro-controllers, host software, interfaces and system integration
Lead implementation and validation of image-processing algorithms developed by the algorithm team
Drive technical planning, design reviews, integration, debugging, risk management and execution
Stay hands-on through selected complex or quality-critical tasks to maintain deep system understanding
Coordinate closely with algorithms, electronics, sensor and system teams

We are looking for a highly experienced Quantum Control Systems Engineer (Application Validation Team) who embodies ambition and positivity. Someone who can passionately take ownership of their responsibilities, collaborating effectively with remote teams to not only meet but exceed our objectives and fulfill the evolving needs of our expanding customer base.
As a Quantum Control Systems Engineer on the Application Validation Team, you will be responsible for validating the software and hardware systems that drive quantum computing operations, ensuring that programs ranging from calibrations to error correction procedures perform as expected on all our quantum controller hardware. This includes designing, implementing, and testing scalable software and hardware frameworks across various qubit types, as well as developing tools that support the validation and execution of control software across different configurations and execution platforms.
Your role will also involve developing a robust software infrastructure that automates the validation process, integrates with real hardware systems, and supports continuous integration (CI) and continuous deployment (CD) pipelines.
This is an exciting opportunity to work at the forefront of quantum computing technology while ensuring the performance, reliability, and scalability of cutting-edge control systems.
Join us in this exciting journey to redefine the future of quantum computing.
Responsibilities:
Quantum Computing Routine Validation: Validate quantum computing programs on our quantum controllers, including calibration procedures, error correction routines, and other algorithms, ensuring they meet the required performance standards.
Scalable Routine Design: Design and implement scalable quantum routines in Qua and other quantum computing languages, optimizing various qubit types and quantum computing architectures.
Framework Development: Develop tools and frameworks that support validation, ensuring scalability and integration into our hardware and software development process.
Automated Testing and CI/CD Integration: Build and maintain automated testing systems, incorporating CI/CD processes to ensure seamless integration and validation of quantum control software on real hardware.
Data Analysis: Analyze measurement data from quantum controllers, using this data to improve implementations across the whole software stack.
Cross-Functional Collaboration: Work closely with quantum physicists, customers software engineers, and hardware engineers to troubleshoot issues, refine quantum routines, and ensure the overall system's performance.

This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.

This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.

What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server).
Take models from research and turn them into production-ready, reliable components deployed on vessels.
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing.
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination.
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization.
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew).
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating.
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems.
Define and maintain clear interfaces between research code and production systems.
Work closely with research and backend teams to integrate new models into production systems.
Continuously improve system efficiency and reliability under hardware and runtime constraints.

we are seeking a networking software engineer to join our rdma transport software team, driving the development of next-generation rdma solutions for ai, cloud, hpc, and Storage. you will research and develop innovative transport algorithms that push the limits of performance and scalability. you will work in a fast-paced, collaborative environment alongside talented engineers from around the world, supporting the data needs of the world's largest enterprises
what you'll be doing:
take part in research, design, and development of advanced rdma transport mechanisms and algorithms, enhancing performance, reliability, and scalability.
collaborate closely with hardware engineers, software developers, and system architects to align on project objectives and requirements.
keep up with industry trends and emerging technologies, integrating new ideas and innovations into the development process

We are seeking for a passionate and skilled Validation Engineer to join our core R&D team. As a Validation Engineer, you'll play a critical role in ensuring the quality, reliability, and performance of our state-of-the-art quantum control systems. You will design, develop, and execute validation plans for complex hardware-software systems, contributing directly to the advancement of quantum technologies.
This role is ideal for engineers with good programming skills, a strong technical culture, and a passion for working at the intersection of software, hardware, and quantum science.
Main Responsibilities:
Design and Implement Validation Methods: Design, implement and execute comprehensive validation test plans for our quantum control platforms and solutions
Automated Tests and Automation Frameworks: Contribute to the development of automated testing infrastructures to streamline validation processes and implement system tests based on the defined test plans
AI/ LLM Tools: Apply AI/LLM tools to accelerate test code generation and continuously improve the validation toolchain, driving measurable gains in engineering productivity
Data Analysis: Collect, interpret, and document data from system tests/experiments to assess system performance and identify areas for improvement
System Debugging & Troubleshooting: Identify, reproduce, and analyze issues across system components with other engineering teams
Collaborate Across Teams: Collaborate closely with R&D and product teams to define test coverage and quality acceptance criteria
Release & Quality Assurance Process: Participate in regression testing and CI/CD for new feature rollouts and product releases
Maintain and Improve Test Setups: Oversee the setup, calibration, and enhancement of test equipment and environments.

Required Design Engineer, Edge AI, 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.
In this role, you will work to shape the future of an Edge-AI product, bringing high-performance intelligence to the edge. You will have an opportunity to drive distributed inference technology that powers real-time systems where latency and reliability are mission-critical.
You will be part of a team that pushes boundaries, developing robust, autonomous solutions that define the next generation of intelligent infrastructure and hardware for the edge. You will contribute to the innovation behind products that transform industries, leveraging your expertise in system-level integration and localized processing to deploy complex AI models across sophisticated hardware platforms, ensuring intelligence is embedded exactly where the action happens.
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
Lead a complex ASIC subsystem.
Understand how it interacts with software and other ASIC subsystems to implement groundbreaking data center.
Define high-performance hardware/software interfaces. Write micro architecture and design specifications.
Define efficient micro-architecture and block partitioning/interfaces and flows.
Collaborate closely with software, verification, and physical design stakeholders to ensure the designs are complete, correct, and performant.