AI Engineer jobs in Herzliya

Description Mentee Robotics, now part of Mobileye, brings world-class robotics expertise, together with Mobileye's decades of leadership in computer vision, machine learning, and autonomous driving technologies. Building on that foundation, Mentee by Mobileye is creating the "MenteeBot", the AI-first humanoid robot that combines perception, reasoning, learning, and advanced dexterous manipulation, designed to work alongside people in their everyday lives, at the workplace and in the home. At Mobileye, our technologies power more than 230 million vehicles worldwide and have helped shape the future of autonomous mobility. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for real life. Responsibilities You will build agentic systems for robotics: LLM- and VLM-based agents that plan tasks, call robot skills as tools, verify outcomes and recover from failure, along with the harnesses that evaluate them in simulation and on the robot. You will develop advanced data-generation methods for deep learning models, combining 3D simulation, reinforcement learning and spatial agents to produce realistic, diverse training data at scale. You will reconstruct real environments and objects with Gaussian splatting and 3D computer vision, and bring them into simulation with correct geometry, so our models train where they will be deployed. You will take this work from prototype to production-grade pipelines on distributed GPU compute. Requirements • B.Sc. in Computer Science, Engineering, or a related field. • 4+ years of hands-on experience in machine learning, computer vision, or robotics software engineering. • Python Expertise: Extensive experience and strong proficiency in Python, a must-have. • Deep learning: Proven experience building and scaling deep learning pipelines (PyTorch), beyond just using existing ones. • Breadth: Hands-on experience in at least one of agentic LLM/VLM systems, simulation/RL data generation, or 3D reconstruction, and familiarity with the others. Advantages • M.Sc. or Ph.D. in Computer Science, Robotics, Computer Vision, or a related field. • Experience with robotics simulators (e.g. Isaac Sim / Isaac Lab, MuJoCo), reinforcement learning, or sim-to-real transfer. • Experience with Gaussian splatting / NeRF, SfM/SLAM (e.g. COLMAP), or meshes for simulation. • Experience applying foundation models to robotics: VLM planners or verifiers, VLA models, open-vocabulary perception. • Comfortable working in cloud and distributed environments (e.g. AWS, SLURM) and with ROS 2 on real robotic platforms.

Description If you've ever dreamt of being there when it all started, this one's for you. At Zeroport, we're rethinking how humans and AI agents securely access and interact with critical systems. As AI becomes more autonomous, controlling what it can access is no longer enough. We're pioneering Least Agency: limiting what AI agents (and humans) can actually do, and enforcing those boundaries independently through physical containment. Our approach combines purpose-built hardware, robust software, and non-IP connectivity to enable secure, real-time work for both AI agents and humans, without exposing the protected network. It sounds bold, we know. That's exactly the point. Who We Are Zeroport is pioneering Least Agency for AI and human network access. Our hardware-enforced architecture creates physical boundaries between AI agents, human users, and critical systems, limiting what they can reach and do by design. We're a focused, technical team with a strong builder mentality, moving fast to redefine how humans and AI securely interact with the world's most critical systems. About the Role We're hiring a senior AI Engineer to join our AI team building our autonomous AI agent and helping extend AI capabilities across the company. The agent runs on NVIDIA hardware integrated inside our purpose-built platform, watches up to 200 concurrent video streams from our hardware-isolated remote access solution, and is the only path to compliance and threat detection in an environment that intentionally blocks every traditional monitoring channel. Larger deployments span multiple edge units coordinating across sites, and the whole system ships into fully air-gapped customer networks — updating, learning, and evolving without ever touching the cloud. This is not a wrap-a-model-in-an-API role. You'll work on real production-grade agent systems, deep multimodal inference at the edge, and the infrastructure that makes both ship and scale. What You'll Do • Design and ship our agent systems end-to-end — perception, reasoning, memory, retrieval, and the loops that connect them. Production agents, not prototypes. • Optimize multimodal inference for real-time operation at the edge — model choice, quantization, and batching to hit our latency and concurrency budgets. • Design embedding pipelines, vector storage, and hybrid retrieval that power the agent's search, behavioral analytics, and rule generation. • Architect how multiple edge units coordinate at scale — sharing context, correlating activity, and behaving as one coherent system for our largest deployments. • Build the agent's air-gapped lifecycle — updating, learning, and evolving entirely inside customer private networks with no cloud connectivity. • Run focused research on new open-source models and inference frameworks, and bring back insights and prototypes that inform our roadmap. Plus occasional cross-company AI projects across the rest of the company. Requirements Who You Are We care about a particular mindset more than any specific item on a checklist. The person who'll thrive here is someone already living inside the modern AI stack - not planning to start. You read model release notes the way other people read the news. You've built real things with new tools the week they came out. Agentic dev workflows aren't something you've heard about; they're how you already work. When a new model drops, your first instinct is to put it on the bench. And underneath all of it, you're a builder - you ship, you write clean software, and you think about latency, cost, and what the user actually needs. What We're Looking For • 6+ years of software engineering experience, with the last few focused on AI / ML systems • Deep, hands-on experience designing and shipping agent systems in production - not demos. You understand agent architectures, memory, tool use, evaluation, and the failure modes that matter at scale. • Strong fundamentals in embeddings, RAG, and hybrid retrieval, with real experience designing vector storage and retrieval pipelines for production use • Deep production backend foundations - strong Postgres knowledge (functions, triggers, indexes, extensions, atomic operations, and similar depth), real-time client channels (WebSockets, SSE), async and event-driven backbones (pub/sub, queues, background tasks, webhooks), the ability to design systems and features around multithreading and multiprocessing, and dynamic resource management for high-throughput, latency-sensitive workloads. • Excellent architecture instincts and strong Python - you write code that scales and that other engineers can build on • Product sensibility - you can reason about trade-offs and what's worth building, not just what's technically possible Nice to Have • Experience with vision-language models and multimodal systems • Experience running AI workloads on edge hardware (Jetson, NVIDIA accelerators, custom inference rigs) • Familiarity with vLLM, TensorRT, or similar inference stacks; quantization and model optimization • Experience with video streaming technologies (WebRTC, GStreamer, STUN/TURN) • Background in networking, cybersecurity, or systems-level Linux • Experience with model fine-tuning and dataset construction Why Join Us • Be part of designing innovative solutions for some of the toughest challenges in network security • Flexible work setup, minimal bureaucracy • Real ownership and impact from day one • A collaborative and innovative work culture • Competitive salary and benefits Let's build it together! Even if you don’t meet every requirement – we’d still love to hear from curious, motivated people.