As an MLOps Team Leader, you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.

What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power our AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

We are looking for a highly driven and experienced AI Engineer Team Leader to manage and mentor a core team of engineers while remaining 50% hands-on. In this critical role, you will lead the development of our enterprise Agentic AI platform, blending deep technical expertise in AI agent development with strong engineering leadership.
As a Team Leader, you will drive the technical agenda, plan sprints, and collaborate closely with Product Managers and cross-functional partners to turn powerful capabilities into reliable, safe, and fast product experiences. You must thrive in a high-pressure, dynamic startup environment characterized by a fast pace and frequent pivots, ensuring your team remains focused, agile, and aligned with business goals while executing at the highest level.
You won't just manage - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily, and iteration in front of enterprise customers.
Responsibilities
Team Leadership & Management (50%): Manage, mentor, and grow a team of AI and software engineers. Oversee task allocation, sprint planning, and daily agile ceremonies.
Hands-On Engineering (50%): Actively code, design, and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Technical Strategy & Architecture: Drive the technical agenda, architecture decisions, and best practices for developing scalable, LLM-driven applications grounded in our knowledge graph.
System Integration: Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Production Excellence: Build evaluation harnesses, guardrails, and safety/bias checks. Optimize agents for latency, cost, and reliability at enterprise scale. Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Cross-Functional Collaboration: Work intimately with Product Management, Data, and Design teams to translate customer needs into agent capabilities, define roadmaps, and prioritize tasks.
Agility & Execution: Lead the team through frequent pivots and rapid development cycles, ensuring high-quality delivery under pressure in a fast-paced startup environment.

We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

Join our mission to build and scale the engineering platform behind a leading SaaS cybersecurity solution trusted by enterprises worldwide.
We are looking for a passionate DevOps Group Lead. You'll lead a strategic engineering organization responsible for the platforms, infrastructure, and automation that power our software delivery lifecycle. You'll manage four Team Leaders and their engineering teams, driving innovation across CI/CD, Kubernetes, AWS, developer platforms, and cloud operations while enabling fast, secure, and reliable software delivery.
This is a leadership role for someone who combines strong technical expertise with exceptional people leadership and a passion for building high-performing engineering organizations.
How will you make an impact?​
Lead, mentor, and develop 3 Team Leaders and their engineering teams, fostering a culture of ownership, collaboration, and continuous learning.
Define and execute the DevOps and Platform Engineering strategy supporting a large-scale SaaS cybersecurity platform.
Own the architecture, scalability, availability, security, and operational excellence of our cloud infrastructure and engineering platforms.
Drive the evolution of modern CI/CD pipelines, Kubernetes platforms, Infrastructure as Code, GitOps, and developer self-service capabilities.
Partner closely with Engineering, Product, Security, Architecture, and R&D leadership to accelerate software delivery while maintaining the highest standards of security and reliability.
Lead cloud-native initiatives with a strong focus on AWS, Kubernetes, automation, and platform standardization.
Establish engineering metrics, operational KPIs, SLOs, and continuous improvement initiatives across the organization.
Champion DevSecOps best practices and embed security into every stage of the software delivery lifecycle.
Lead organizational planning, hiring, budgeting, prioritization, and execution while supporting the growth and development of future engineering leaders.

Required Data Engineering Manager
Data, Ramat Gan, Israel (Hybrid)
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities:
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

Required Algorithm Team Lead - Geometric Data Infrastructure
About the team:
The AV Sensing group is responsible for the critical and challenging task of object detection and scene comprehension using LiDAR and Radar sensors. Our team develops scalable infrastructure and algorithmic solutions for processing, validating, and understanding complex 3D sensor data.
What will your job look like:
Lead and mentor a team of ~5 Algo and Software Developers while remaining hands-on and closely involved in technical and algorithmic challenges.
Design and build scalable Python libraries, data workflows, validation and monitoring systems for spatial data.
Develop algorithms and geometric tools for 3D data processing, sensor calibration, coordinate transformations, and spatial relationships.
Build and maintain development infrastructure, including databases, dashboards, CI/CD pipelines, and automated documentation.
Take ownership of complex algorithmic challenges from research through production, while collaborating with cross-functional teams to integrate solutions into the broader system.

We are looking for a Product Engineer to own and ship the products that put this capability in the hands of engineers, data scientists, and researchers.

What you'll do
Own product features end-to-end: scope, build, ship, measure, and iterate - across CLI, IDE integrations, web surfaces, and the AI pipeline behind them.

Talk directly to users - engineers, data scientists, ML practitioners - and let their feedback shape what you build next.

Define what AI-powered code optimization and verification feels like as a developer experience: the interaction model, the feedback loops, the trust signals. There is no established playbook; you will create the conventions.

Craft interfaces that feel fast, focused, and effortless for technical users who have zero patience for friction.

Collaborate with researchers to translate model breakthroughs into polished, reliable tooling that developers can depend on in production.

Build evaluation infrastructure and product metrics that measure whether the tools are actually getting better.

Work directly with the founding team on product strategy and roadmap.

we are looking for a Embedded Software Group Lead- Interceptor Systems.
As the Software Group Lead, you will be the primary architect and execution lead for a cutting-edge missile interceptor system. This is a high-stakes executive role requiring a rare blend of low-latency embedded engineering and high-level Command & Control (C2) orchestration. You will be responsible for building a multi-disciplinary software team from the ground up, defining the software lifecycle, and ensuring the seamless integration of missile subassemblies with ground-based mission control.
We are looking for a "builder" mentality, capable of switching between high-level architectural strategy and driving end-to-end delivery from concept to field deployment.