דרושים » הנדסה » Senior Robotics Algorithm Engineer - Autonomous Navigation

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 looking for a Senior Software Engineer.
What you will do:
Build and evolve core backend services that orchestrate field data acquisition across distributed, real-world environments.
Design and implement asynchronous, pipeline-driven systems for real-time data ingestion, validation, and processing.
Own critical system components end-to-end, with responsibility for correctness, performance, resilience, and behavior under real production conditions.
Lead architectural decisions and technical direction, driving improvements in scalability, robustness, and long-term system clarity.
Work hands-on with live production systems developed and deployed remotely to edge devices in the field, including releases, field experiments, deep debugging, and on-call support.
Collaborate closely across disciplines - system engineering, algorithms, hardware, frontend, and operations - to deliver cohesive, end-to-end solutions.
Raise the engineering bar through high-quality code reviews, design discussions, and by shaping best practices within the team.

We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

Our detection engine is a large Python codebase running PySpark over cloud, SaaS, and identity data at scale on Databricks. Youll own its engineering quality - hardening whats there and extending it - working alongside the cyber investigators who define what it should catch.

In this role, you will:

Harden and extend a large production Python codebase: refactoring, module and API design, typing, test coverage.

Own and optimize critical PySpark workflows processing massive security datasets across multi-cloud environments - correctness and cost both.

Design the data models and queries the engine depends on, and fix the slow ones.

Work directly with cyber investigators to turn attacker behavior into detection logic that holds up in production.

Build with AI as a core tool: AI coding agents daily, and the AI tooling the team runs on - agentic and automated workflows (n8n or similar) and LLM-backed services on Bedrock or vendor APIs.

Raise the bar on engineering practice - code review, CI, and the standards the team holds each other to.

Contribute to architectural decisions and technical direction as the platform evolves.An empty job that is used for creating requisitions 'from scratch'

We are looking for an AI Engineer to build the systems that drive this: AI agents that investigate vulnerabilities, generate and validate code fixes, and continuously refine their performance. In this role, youll work at the intersection of AI engineering, security automation, and rigorous evaluation to translate cutting-edge models into dependable production tools.

Responsibilities

Build and evolve production AI agent pipelines for CVE research, patch generation, validation, container image remediation, and end-to-end merge requests.

Design the agent capabilities behind those workflows: prompts, tools, model selection, context, guardrails, and integrations.

Build the feedback loops that make our systems better: tracing production runs, creating datasets, defining evals and scorers, and using results to guide iteration.

Analyze real-world performance to answer the questions that matter: Did this change improve patch success, quality, latency, or cost Can we prove it?

Operate what you build in production across Kubernetes, Argo Workflows, AWS, and GitOps.

Partner closely with Product and engineering to focus on the customer problems with the highest security impact-and ship quickly.

Our Network Architecture, Modeling and Performance Insights group is seeking a skilled and driven AI Network Modeling Engineer to conduct advanced network research and optimization while utilizing and enhancing our advanced simulation tools.

In this role, you will be a key contributor to defining the architecture and improving network performance for AI and High Performance Computing (HPC) workloads. You will be responsible for modeling advanced network architectures, topologies, configurations, logic and traffic patterns, and analyzing their effect on end to end performance. You will develop expertise in our simulation tools and contribute directly to their development road map and prioritization, develop core features in the simulator, and expose the capabilities to additional users. You will take part in complex architecture decisions, define and verify the modeling assumptions, and put them to the test vs. real HW and SW performance. If you're passionate about tackling intricate challenges and contributing to comprehensive systems and working on innovative solutions, we want to hear from you.

What you'll be doing:

Directly impact the architecture of our next generation AI and HPC offerings through modeling, simulation and analysis.

Deep dive into network behavior for training and inference use cases under advanced network topologies, configurations and traffic patterns which represent real life AI workloads, and analyze their effect on the systems performance. Develop advanced simulation solutions while contributing modular and scalable code.

Actively support the HW and SW development life cycles, map existing and candidate features into the simulation domain to enable their analysis, impact assessment and optimization.

Take full independent ownership of the performance modeling roadmap for a defined set of features. Interface directly with internal clients, communicate the analysis conclusions effectively and iterate on them. Drive projects from concept to completion.

Improve the quality of the simulation as a software product, ensuring robustness and reliability.

As an AI Algorithm Engineer at our company, youll design and implement advanced algorithmic workflows that power our data digestion pipelines and conversational AI agent experience. You will:
Architect and build workflows that turn raw, unstructured data (e.g., PDF documents and ultra high-resolution architectural drawings) into meaningful, structured context for downstream analysis.
Combine techniques from classical NLP, computer vision, unsupervised learning, and graph theory to build robust end-to-end pipelines - not just standard LLM API calls, but intelligent decomposition, structuring, and context engineering.
Develop AI agent workflows that let customers explore, query, and reason about their data naturally and reliably.
Build strong evaluation infrastructure to benchmark and continuously improve both classical algorithmic components and LLM-based workflows.
Work primarily in Python, and collaborate across systems and services in TypeScript when needed.
Move fast from prototype to production, while maintaining correctness, scalability, and measurable quality.

We are looking for a Sr. Staff Backend Engineer to join our team. This is a Hybrid (Ramat Gan) role, reporting to the Manager, Software Engineering in the Exposure Management & Security Operations department. Avalor, now part of Zscaler, powers the data foundation behind Security Operations platform, ingesting, unifying, and contextualizing data from hundreds of security and business tools to power security modules that deliver actionable insights and measurable risk reduction to our customers. In this role, you'll own complex backend systems that sit at the heart of our data platform, designing and building services that ingest, process, and move massive amounts of data reliably and at scale for enterprise customers worldwide.

What youll do (Role Expectations)

Developing and maintaining high-quality, scalable backend services within a microservices architecture using Java/Spring Boot and Python
Designing and building data pipelines and ETL workflows that ingest, transform, and unify data from diverse sources at enterprise scale
Leading solutions from scratch to production; creating technical designs, driving architectural decisions and taking full ownership of complex projects - from design and implementation through deployment, monitoring performance, reliability and cost, and proactively driving improvements
Collaborating closely with cross-functional partners - product managers, frontend/backend engineers and UX designers
Serving as a technical anchor for the team - leading design discussions, setting engineering standards, and driving best practices across the codebase
Who You Are (Success Profile)

You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback-knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

Were now looking for a world-class Senior Software Engineer to help architect and build the core systems behind our AI security engine.
As part of our AI Cybersecurity team, youll design and build the infrastructure and agent workflows that power security platform. This is a full-lifecycle engineering role, covering backend systems, AI agent development, and product integration, with a focus on building workflows that are reliable, scalable, and production-ready.
What Youll Do:
Architect and build backend infrastructure powering secure, scalable AI workflows.
Develop core systems for multi-agent reasoning, retrieval pipelines, and tool execution.
Productionize AI models and agent workflows with strong reliability and performance guarantees.
Integrate AI services across the product stack, from backend APIs to user-facing workflows.
Own systems end-to-end: design, implementation, deployment, monitoring, and iteration.
Apply secure engineering principles across everything you build, from APIs and data flows to infrastructure and deployment.