דרושים » מדעים מדוייקים » Senior Computer Vision Algorithms Engineer - Deep-Tech AI Systems

Come join the company team as a Staff AI Engineer.
Our Data Exchange group is responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all our company products.
You will utilize your skills to help develop and maintain backend services leveraging AI and machine learning models, using both analytical algorithms and deep learning approaches, to acquire data from financial institutions on behalf of our users.
Responsibilities
Lead and apply best practices in AI driven software lifecycle management, from ideation, through development and evaluation to production deployment.
Build a backend service with AI in its core at scale (millions of users and requests daily)
Collaborate with stakeholders to define success criteria and align model metrics with business goals
Work side-by-side with product managers, business analytics, data scientists, and backend engineers in enabling AI solutions for business use cases
Explore the state-of-the-art technologies and apply them to deliver customer benefits.

Required AI Architect
Position Overview:
As the AI Architect for our SaaS Platform & Products, you will define and drive the end-to-end AI architecture that powers our cloud AI platform and product capabilities, while ensuring strong alignment with security, privacy, reliability and cost-efficiency requirements. You will partner closely with engineering leaders, product management, data science, security and operations to translate business needs into a scalable, governed and AI platform that accelerates innovation across multiple product lines.
This is a hands-on architecture role: you will set technical direction, run architectural reviews, and build prototypes to validate technology choices and de-risk delivery.
Key Responsibilities:
Own the AI Vision: Take end-to-end ownership of the AI architecture across, including our cloud AI platform, agentic AI infrastructure, and on-prem/hybrid AI deployments.
Architect an AI Platform for SaaS Products: Define reference architectures and shared building blocks (e.g., AI gateways, orchestration runtimes, memory/RAG systems, vector search, evaluation frameworks, observability, and guardrails) that can be adopted consistently across products and teams.
Cost Optimization and Scalability: Provide architectural leadership to ensure AI systems are designed for cost efficiency and scalability, actively identify and implement opportunities to optimize cloud spend (FinOps), improve utilization, and meet latency/SLO targets.
Product-Centric Collaboration: Collaborate with engineering, product, data science, security, and operations teams to translate product requirements and business needs into a strategic AI architecture that drives measurable product value.
Technology Evolution and Prototyping: Evaluate new technologies, tools, and methodologies to continuously improve our AI systems, build prototypes and proof-of-concepts to validate approaches and accelerate decision-making.
Technical Reviews, Standards and Mentorship: Lead technical design reviews and provide guidance on best practices and emerging technologies. Act as a technical authority and mentor, fostering a culture of engineering excellence and pragmatic delivery.
AI Governance, Privacy and Security: Ensure AI capabilities comply with data privacy, security, and ethical AI guidelines. Partner with security and legal stakeholders to implement governance controls and risk mitigations appropriate for regulated environments.

Join our companys Content Safety team as a Staff AI Scientist, where youll build the intelligent infrastructure that keeps our global platform secure. We're looking for a specialist to design and deploy production-grade GenAI solutions that moderate content at scale. From pioneering automated labeling workflows to securing AI-generated outputs, your work will define the safety standards for every product in the company portfolio.
Responsibilities
Architect Robust Moderation Systems: Lead the design and deployment of sophisticated, multi-modal content moderation engines to detect and mitigate abusive content across our companys diverse product ecosystem.
Drive LLM Strategy: Direct the fine-tuning and optimization of state-of-the-art Transformers and Large Language Models (LLMs), balancing high-precision accuracy with production-scale efficiency.
Pioneer Agentic Workflows: Research and integrate advanced GenAI patterns-including Retrieval-Augmented Generation (RAG) and Agentic AI-to revolutionize automated data labeling and complex classification taxonomies.
Cross-Functional Leadership: Partner closely with ML Engineers, Product Leads, and Policy Experts, to help ensure AI systems aren't only technically superior - but also ethically grounded and compliant with global safety standards.
Technical Evangelism and Research: Act as the teams North Star by staying at the bleeding edge of AI research, translating academic breakthroughs into practical, "production-first" content safety strategies.
Communication and Governance: Standardize high-quality documentation and model governance. You will translate complex technical architectures into clear, actionable insights for both executive stakeholders and technical peers.
Team Upskilling and Mentorship: Serve as a force multiplier by mentoring junior and senior scientists, conducting rigorous code/design reviews, and fostering a culture of technical excellence.

We are seeking an R&D Lead to lead the development for Agentic Commerce, a brand new product. The product focuses on owning the visual and semantic layer that AI agents rely on to understand, rank, and present products. We are a small, fast-moving, and highly independent team with full end-to-end ownership. The opportunity ahead is large: the front door of commerce is shifting from websites to AI agents, and merchants must adapt to be discovered, selected, and converted inside agent-driven experiences.
Responsibilities
Lead and be accountable for all development efforts, with a co-founder / CTO-level mindset
Co-lead the pod alongside the GM as a true counterpart
Build a deep understanding of how AI agents consume product data, media, and signals, and how merchants win selection and conversion in this new paradigm
Starting as a solo developer, you will be responsible for designing and shipping an AI-native product, growing a team when needed
Leverage platform to get to market quickly, building only what meaningfully advances learning and traction
Continuously adjust technical direction as agent behaviors, protocols, and market assumptions evolve

Required AI Platform Engineer
Position Overview:
We're assembling a small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As an AI Platfrom Engineer, you will be a critical architect of the technological infrastructure that brings our most ambitious GenAI concepts to life, transforming our digital intelligence solutions through cutting-edge AI innovation.
Build advanced AI platform that operates both as a cloud SaaS and as a fully self-contained on-prem / edge deployment, designed for privacy-sensitive and security-critical environments, at the intersection of backend development, AI integration, DevOps, and open-source systems engineering.
You will be part of the core team responsible for adapting, hardening, and operating our SaaS architecture in on-prem and single-node environments (on Prem servers, laptops). Working closely with architecture and product management and play a key role in making complex AI systems deployable, reliable, and operable outside the cloud.
Key Responsibilities
Platform & Application Engineering:
Adapt cloud-native AI services to on-prem and edge deployments (single node, no managed cloud services).
Build and maintain full-stack components: Backend APIs (Python / Node.js), Lightweight UIs or internal tools when needed, Ensure services are stateless, configurable, and portable across environments.
AI & Open-Source Integration:
Integrate and operate open-source LLMs for:
RAG pipelines
Agentic workflows
Tool calling and orchestration
Work with: Embedding models, Vector databases (local and embedded modes), Analytical engines (e.g., embedded SQL / columnar systems), Optimize inference for CPU / single-GPU environments (quantization, batching, caching).
DevOps & Runtime Engineering (Strong Focus):
Package services into portable Docker containers usable in:
On-prem servers (Kubernetes)
laptop / edge devices
Implement in-process scaling strategies (worker pools, task queues, batching).
Build simple, reliable deployment and startup flows (no heavy orchestration).
Manage configuration, secrets, logging, and observability in constrained environments.
Systems & Reliability:
Design for: Offline operation, Limited resources, Predictable performance
Implement graceful degradation between: SaaS mode, On-prem server mode, Single-node / laptop device mode, Debug complex interactions across AI models, storage, and runtime systems.

We are looking for a Mid-level Data Engineer to join our growing Data/MLOps team. The team is focused on building a Data/MLOps infrastructure to support the development of ML and AI algorithms for our next generation iTero scanners.
The position is suited for engineers who like to work with data, build data infrastructure and wish to support algorithm engineers.
The position is based at our Petah Tikva or Caesarea site.
Key Responsibilities
Own significant components in a data infrastructure for AI/Algorithm development.
Work with large image/3D datasets to support the development of real-life ML/AI solutions.
Work with ML / AI engineers to identify future challenges and solutions.
Own the quality of data ingestion pipelines over time.
Consistently demonstrate innovative thinking, strong partnership and high work ethics.