דרושים » הנדסה » Software Engineer - Edge Inference

At our company, we build AI-powered vision systems that enhance safety and decision-making for some of the worlds largest vessels.
Our platform processes live video streams from multiple onboard cameras to provide real-time situational awareness, detecting and tracking marine objects, even in low visibility and highly congested environments. These systems directly support navigational decisions and help prevent collisions, reduce human error, and improve operational efficiency.
Our systems are already deployed across thousands of vessels and have processed hundreds of millions of nautical miles of real-world data, operating in unpredictable and safety-critical conditions.
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.

our company is a global leader in control systems for our computing-a field on the verge of exponential growth.
our innovative hardware and software mark a groundbreaking approach to our computer control, scaling from individual qubits to expansive arrays of thousands.
at the core of qm lies a passionate and ambitious team committed to reshaping the construction and operation of our computers. our work is fueled by a deep understanding of customer needs, driving us to deliver unparalleled solutions in this revolutionary field.
were seeking a software system Engineer to ensure seamless operation and integration of our complex, multidisciplinary system. this role spans multiple software domains and interfaces with hardware, logic, and validation teams. youll act as a technical leader, driving design and implementation of system -wide features, resolving intricate integration challenges, and building infrastructure that accelerates development across the software group.
youll thrive here if you love working on large-scale, multi-threaded systems, solving cross-disciplinary problems, and building robust, production-quality solutions for cutting-edge our computing products.
responsibilities
system integration & technical leadership
ensure proper operation and integration of all software components and their interfaces with logic and validation modules.
lead design and implementation of multidisciplinary features, balancing performance, reliability, and maintainability.
investigate and resolve complex system -wide issues and bugs across multiple teams.
infrastructure & tooling
develop and maintain internal tools and infrastructure to enhance development efficiency and integration readiness.
build profiling, debugging, and automation frameworks to support high-quality delivery.
cross-team collaboration
key stakeholder in the definition of interface contracts (apis, protocols, timing/resource constraints) across software and hardware boundaries.
drive integration plans, dry runs, and troubleshooting for system -wide features.
quality & execution excellence
champion clean architecture, code reviews, automated testing, and ci/cd best practices.
ensure documentation (design specs, interface definitions, runbooks) is complete and up-to-date.

Founded in Tel Aviv in 2016, UVeye is a computer vision and data company that creates automatic vehicle inspection systems to encourage road safety and increase transparency across the automotive industry. With key partnerships including General Motors, Volvo, and CarMax among others, our technology is utilized in manufacturing plants, dealerships, wholesale auctions, delivery fleets, security checkpoints, and more. Want to be an essential part of setting the standard for safety in the auto industry? Check out the description below to see if you’re a great fit!
UVeye is seeking a highly skilled Software Engineer to join our R&D team. The ideal candidate will work closely with hardware engineers to create efficient, reliable, and scalable embedded solutions for various applications.
?Here’s what you’ll be doing:
* Implement C++ and Python software for data processing, system-level orchestration, and image acquisition.
* Acquire and manage data streams from sensors and imaging devices.
* Develop and maintain highly efficient C++ Code in a dockerized Linux environment
* Collaborate with HW & FW engineers to ensure seamless integration between software and hardware components.
* Develop software that interfaces with embedded systems and MCU-based firmware.
* Design and maintain data pipelines to ensure reliable transfer of heavy data (images/video) from the edge device to cloud environments.

Required xEngineer (ai-native software engineer)
makes it possible for anyone to succeed online. since 2006, weve grown to around 5,500 employees in 22 countries, launched over 40 products, and serve over 243 million users and their visitors worldwide. here, we push you to innovate, evolve in non-traditional ways, and collaborate. we operate in small teams that work closely together at a high level.
although were already industry leaders in web creation and business, our work is nowhere near done. our goal is to become the main engine of the internet so we can create a more open web for all.
we're proud to be an equal opportunity employer. the company was built around the idea that everyone has the right to be successful, online. this same vision defines us as an employer: creating a work environment where everyone is welcome, and anyone has the right to succeed.
as an xEngineer, youll combine deep technical expertise with system -level thinking and product ownership, applying ai across the development lifecycle to build impactful systems, make thoughtful architectural decisions, and drive technical excellence from idea to production. in your day-to-day, you will:
design and own end-to-end systems and features that serve millions of users, taking responsibility across stack boundaries - from product flows and User Experience to apis, data models, and production systems
apply ai-powered tools and workflows across planning, design, implementation, testing, debugging, and refactoring
work with modern technologies and platforms (e.g., typescript, React, Node.js, JAVA, cloud, and ci/cd), continuously evolving your toolkit with ai-powered tools
lead architectural thinking by making thoughtful trade-offs around scalability, reliability, security, performance, and maintainability
collaborate closely with product managers, designers, and engineers to shape solutions while ensuring production quality, observability, and long-term system health
at the company, we believe our best work happens together. our work model is fully in person, with 5 days a week from our office. flexibility remains a core value at the company and special requests are handled thoughtfully at the team level.
we are engineering at the company - a team of ai-native xengineers with deep expertise in frontend, backend, or mobile, who use ai support to take ownership over projects end-to-end. we work in a fast-paced, dynamic development environment with autonomous teams that never compromise high quality standards. as ai increasingly generates production code, we dedicate more and more of our time developing the skills we believe are critical for today and tomorrow: system design, architecture, scalability, reliability, and security.

we are on a mission to bring identity security everywhere - to every human, machine, and AI agent, both on-prem and in the cloud.
Our unique technology secures identities & access at runtime, in ways that werent possible before. With the broadest identity security platform in the market, trusted by more than 1,000 customers including many Fortune 100 companies, we are uniquely positioned to lead the fast-growing identity security category.
Joining our company means becoming part of a fast-moving team with a culture of innovation and collaboration, that goes above and beyond to help our customers and each other, on a journey to reshape the future of identity security.
We are looking for a Full Stack Software Engineer to join us. As a Full Stack Software Engineer at our company, you will work across the stack, from backend services that process and analyze large-scale security data to a modern frontend that transforms complex information into intuitive, actionable workflows. You will design and maintain high-performance systems that process millions of authentication events daily, ensuring reliability, scalability, and real-time insights. 
Responsibilities
Design and deliver end-to-end features across high-performance systems
Architect and build scalable services for processing, analyzing, and exposing large-scale security data
Develop advanced security engines with a focus on performance, scalability, and reliability
Own features end-to-end, from design through production and continuous improvement
Collaborate closely with product, support, and cross-functional teams to deliver high-impact solutions.

As a Senior/ Principal/ Senior Principal Software Engineer at Cortex Cloud, you will serve as a primary technical architect and visionary for our core communication infrastructure. This role is focused on the critical server-side backbone that facilitates high-scale bidirectional communication between our cloud services and client-side applications.
You will be responsible for the architectural integrity of systems that receive massive data inflows from the field and reliably broadcast intelligence back to millions of endpoints. This is a high-impact leadership role requiring a blend of deep technical mastery in distributed systems and the ability to influence technical strategy across the organization.
Key Responsibilities
Architectural Strategy & Vision: Define and drive the multi-year technical roadmap for our server-side communication infrastructure, ensuring the platform remains resilient and performant under extreme load.
High-Scale Communication Infrastructure: Lead the design and implementation of backend systems optimized for receiving high-scale data from client-side apps and distributing data back to a vast ecosystem of endpoints.
Technical Leadership & Influence: Act as a force multiplier by providing technical guidance to multiple engineering teams, aligning them on shared protocols, architectural standards, and communication patterns.
Drive Engineering Excellence: Champion a culture of high engineering rigor, focusing on deep observability, low-latency data distribution, and runtime stability for mission-critical production environments.
Cross-Functional Collaboration: Partner with Product Management, Infrastructure, and Client-Side Engineering teams to evaluate technical trade-offs, mitigate risks, and ensure seamless end-to-end data flow.
Innovation & Prototyping: Spearhead the evaluation of emerging technologies and lead "proof of concept" initiatives for next-generation transport layers and messaging paradigms.
Technical Mentorship: Invest in the growth of Senior and Staff engineers through deep-dive design reviews, code audits, and hands-on pair programming on the most critical paths.
Strategic Customer Engagement: Support the business by leading technical deep dives with strategic customers, translating complex architectural concepts into actionable confidence for our partners.

Were looking for a senior engineer with strong systems-level thinking and a good understanding of Linux. You should be comfortable working close to the kernel, ideally with experience in eBPF, or with a strong desire to dive into it. Proficiency in C/C++/ Go is essential, and familiarity with networking protocols, TLS internals, or distributed tracing is a strong advantage.
Youll join a high-impact team tackling ambitious technical challenges-like decoding traffic across multiple protocols, and ensuring high-fidelity metrics in complex, real-world environments. Youll be expected to lead design and implementation efforts, contribute to roadmap planning, and collaborate across teams to ensure our solution remains robust, scalable, and frictionless for our users.
This role is a great fit for engineers who thrive on low-level, performance-sensitive problems, and want to shape the future of observability through cutting-edge kernel technology.

We're looking for a Senior AI/MLOps Engineer to join a group that specializes in Security and Networking, and specifically ML, AI and agent development. As a Senior AI/MLOps Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, security architects and DevOps teams to ensure smooth deployment, modeling and optimization of AI models. This role involves creative problem solving alongside engineering teams, and is pivotal for the continued success of AI networking security.

What youll be doing:

Developing, improving and optimizing scalable infrastructure for handling and deploying security and networking AI models and agents in production, ensuring high availability, scalability, reproducibility, and performance.

Optimizing AI models and agents for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Monitoring and deploying agentic systems, LLMs, and ML models in production.

Designing and implementing frameworks/pipelines for AI training, inference, and experimentation.

Collaborating closely with data scientists, security architects and software engineers to operationalize and deploy AI models and agents, including packaging and integration with existing systems. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Collaborating with DevOps teams to integrate pipelines and workflows into the CI/CD process, ensuring flawless deployments and rollbacks.

Building and maintaining monitoring and alerting systems to proactively identify and resolve issues relating to quality, performance and infrastructure.

Implementing access controls, authentication mechanisms, and encryption standards for AI models and data.

Documenting guidelines, and standard operating procedures for MLOps/AI processes and sharing knowledge with the wider team.

Develop proof-of-concepts for new features.

Were building a new orchestration platform for AI datacenters-software that turns a complex, multi-vendor stack of compute, networking, and accelerators into something customers can deploy, operate, and optimize with confidence.
Youll join a small founding team (growing later) where every engineer ships. This is a hands-on architect role in the truest sense: youll own key architectural decisions and write production code 100% of the time, side-by-side with the team.
If you like shaping systems at the whiteboard-to-production level-and you want your decisions to run at scale in real AI datacenters-this is that kind of role.
What Youll Do
Design and build the core of an orchestration platform spanning the full datacenter stack.
Turn real customer needs into crisp system architecture: service boundaries, workflows, APIs, data models, and failure modes.
Implement critical platform components end-to-end: from prototypes and spikes to hardened production services.
Define and evolve platform standards through working code: patterns, libraries, templates, test strategy, CI/CD.
Make pragmatic tradeoffs (performance vs. simplicity, consistency vs. availability) and document the why.
Lead design and code reviews, raising quality while keeping velocity high.

Required CI and Automation Engineer
About the position
As a CI and Automation Engineer leading our Release efforts, you will bridge the gap between pure DevOps/Automation and the final delivery of our AI software stack. You wont just be building pipelines; you will be the technical owner of the release cycle, architecting the automation and branching strategies that ensure our firmware and software are production-ready.
You will act as the Technical Gatekeeper, using your deep-dive coding skills in Python and Bash to build the infrastructure of trust that powers our releases. This role is for a hands-on engineer who wants the strategic responsibility of making the Go/No-Go call based on the very automation they have built. If you are passionate about CI/CD excellence and want to see your code directly impact the delivery of world-class AI hardware, this is the role for you.
Responsibilities:
Release Ownership: Lead the technical execution of release cycles, acting as the primary authority and Gatekeeper for software and firmware delivery.
CI/CD Engineering: Design, implement, and maintain robust CI pipelines (e.g., Jenkins, Bitbucket) tailored for release stability and automated validation.
Hands-on Automation: Develop and maintain tools and scripts (Python, Bash) to automate the entire release flow-from versioning and branching to automated reporting.
Technical Triage: Deep-dive into build failures and integration issues. Analyze logs and code changes to make data-driven Go/No-Go decisions.
Branching Strategy: Define and manage complex Git strategies to ensure smooth integration across multiple versions and hardware targets.
Visibility & Reporting: Provide real-time visibility into release health and quality metrics through dashboards and automated status reports.