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Required Backend Intern
We are the market leader for building the technology behind the most advanced datacenters and AI infrastructure in the world. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud. 
Zerto was founded in Israel and was acquired by HPE about four years ago. Our technology helps over ten thousand companies (hospitals, finance, industry, etc.) worldwide keep their businesses running without disruption by protecting and recovering applications across datacenters and clouds such as AWS, Azure, Google Cloud, IBM Cloud, and Oracle Cloud. 
Joining us means being part of a company that solves real problems for real customers, while giving you the chance to grow, learn, and make an impact. 
What will your work be like? 
Develop backend features in modern C++ for a large-scale, production-grade system.
Investigate and resolve challenging bugs involving distributed systems, concurrency performance, and reliability.
Gain experience with linux, virtualization, storage, networking, and cloud technologies.

Required Backend Intern
Job Description:
We are a market leader in building the technology behind some of the worlds most advanced data centers and AI infrastructure. We help companies connect, protect, analyze, and act on their data and applications wherever they live-from edge to cloud.
Zerto was founded in Israel and acquired by HPE about five years ago. Our technology helps more than ten thousand organizations across healthcare, finance, industry, and other sectors keep their businesses running without disruption. We protect and recover applications across virtualization platforms such as VMware, HPE Morpheus VM Essentials, and Microsoft Hyper-V, as well as cloud platforms such as AWS, Azure, and Google Cloud.
Joining us means becoming part of a company that solves real problems for real customers while giving you the opportunity to learn, grow, and make an impact.
What will your work be like?
Join a Zerto development team working in an Agile/Scrum environment.
Develop new features and solve challenging bugs.
Contribute to a distributed, multi-service system with complex business logic.
Work with a modern, continuously evolving technology stack, including Kubernetes,.NET Core, virtualization APIs, and more.
Use AI throughout the software development lifecycle-including research, design, coding, code reviews, environment provisioning, product deployment, and bug analysis-with tools such as GitHub Copilot, OpenCode, Atlassian Rovo, and MCP servers.

We are looking for a Junior Product Support Specialist to deliver advanced assistance for our software products



Key Responsibilities:

Manage client onboarding and ensure smooth, effective use

Investigate and resolve first and second-level technical incidents

Perform in-depth troubleshooting and identify underlying issues

Support customers through phone, email, and other communication channels

Work with R&D on system-level problems

Required Senior Back-End Developer
Who are we?
We are the agentic layer for enterprise systems where teams and metadata agents plan, change, and govern systems with speed and confidence.
What will you do?
As a Senior Back-End Developer, youll play a critical role in shaping the foundation of our innovative platform. Working alongside a talented team in Tel Aviv, you will:
Design and develop core products and features that empower our users to achieve their goals.
Partner closely with product managers, front-end developers, and other stakeholders to deliver scalable and impactful solutions.
Participate in all stages of the product development lifecycle, from concept and design to deployment and maintenance.
Take initiative in solving complex technical challenges while contributing to the strategic direction of our technology stack.

We are looking for a Senior Mobile Engineer who is passionate about building high-quality products, solving complex technical challenges, and delivering experiences that make a meaningful impact on people's lives. You will partner closely with Product, Design, Data Science, and Engineering teams to take products from concept to production while helping shape the future of our platform.
You will join an experienced engineering organization building products used by people around the world, working in an AI-augmented development environment that embraces modern tools to accelerate delivery, improve code quality, and increase engineering effectiveness.
Our Technology Stack: React Native, React, TypeScript, Redux, Scala, Play Framework, Microservices, AWS, Docker, Kubernetes, MongoDB, Redis, PostgreSQL, Spark, Elasticsearch, Kafka, and more.
Responsibilities:
Build and deliver scalable, reliable, and maintainable software that powers products used daily by members around the world.
Design and develop frontend and backend solutions with a focus on performance, scalability, and user experience.
Create reusable frontend architecture, components, and engineering patterns that improve development velocity and consistency.
Partner with Data Science teams to integrate algorithms and data-driven capabilities into new and existing products.
Collaborate closely with Product Managers, Designers, Data Engineers, and fellow engineers throughout the full product development lifecycle, including discovery, design, implementation, experimentation, and iteration.
Take ownership of projects from technical design through production deployment and ongoing optimization.
Contribute to architectural decisions and continuously improve engineering standards, processes, and platform capabilities.
Leverage AI tools throughout the software development lifecycle to accelerate development, improve code quality, and increase team productivity while maintaining strong engineering judgment.

We are looking for a Senior Full-Stack Engineer who specializes in Mobile application development and is passionate about building high-quality products, solving complex technical challenges, and delivering experiences that make a meaningful impact on people's lives. You will partner closely with Product, Design, Data Science, and Engineering teams to take products from concept to production while helping shape the future of our platform.
You will join an experienced engineering organization building products used by people around the world, working in an AI-augmented development environment that embraces modern tools to accelerate delivery, improve code quality, and increase engineering effectiveness.
Our Technology Stack: React Native, React, TypeScript, Redux, Scala, Play Framework, Microservices, AWS, Docker, Kubernetes, MongoDB, Redis, PostgreSQL, Spark, Elasticsearch, Kafka, and more.
Responsibilities:
Build and deliver scalable, reliable, and maintainable software that powers products used daily by members around the world.
Design and develop frontend and backend solutions with a focus on performance, scalability, and user experience.
Create reusable frontend architecture, components, and engineering patterns that improve development velocity and consistency.
Partner with Data Science teams to integrate algorithms and data-driven capabilities into new and existing products.
Collaborate closely with Product Managers, Designers, Data Engineers, and fellow engineers throughout the full product development lifecycle, including discovery, design, implementation, experimentation, and iteration.
Take ownership of projects from technical design through production deployment and ongoing optimization.
Contribute to architectural decisions and continuously improve engineering standards, processes, and platform capabilities.
Leverage AI tools throughout the software development lifecycle to accelerate development, improve code quality, and increase team productivity while maintaining strong engineering judgment.

We are looking for an experienced QA Engineer who is passionate about quality, adversarial thinking, and bug hunting. You will own the quality of your product domains from feature planning through production release, working closely with Product, Design, and Engineering teams throughout the development lifecycle.
In this role, you will design comprehensive test plans, execute exploratory, functional, regression, and end-to-end testing across mobile and backend systems, and drive issues to resolution. You will take ownership of the quality of your domain, prioritize risks, communicate findings clearly across the organization, and continuously improve QA processes and testing methodologies.
We are looking for someone who enjoys challenging assumptions, works independently, embraces AI tools to improve productivity, and has a strong sense of ownership over product quality.
Responsibilities:
Design and execute comprehensive test plans for new features and enhancements.
Perform exploratory, functional, regression, and end-to-end testing across mobile applications and backend services.
Use AI tools to improve productivity, testing efficiency, documentation, and problem solving.
Own the quality of assigned product domains from feature planning through production release.
Identify, investigate, prioritize, and communicate defects and product risks across teams.
Collaborate closely with Product, Design, and Engineering to ensure high-quality feature delivery.
Drive continuous improvements to QA processes, testing methodologies, and product quality.
Take ownership of your domain by proactively identifying risks, proposing solutions, and driving quality initiatives.

We're backed by tier-1 global VCs, led by second-time founders, and moving fast because the problem demands it. There are no silos here. No "that's not my area." If it ships, you own it.
We're hiring a full-stack software engineer who wants end-to-end ownership - backend, frontend, infrastructure touchpoints, and AI-driven workflows.
If you're looking for narrow scope or strict boundaries, this is not the role. If you like building real systems and taking responsibility for outcomes, read on.
What you'll do:
Own systems end-to-end - infrastructure, pipelines, and their behavior in production
Run and evolve our cloud infrastructure - Kubernetes, Kafka, Terraform, GitOps (AWS today, multi-cloud ahead)
Build the data backbone - ingestion, streaming, and pipelines into our lakehouse that stay correct and affordable as volume grows
Build AI-native engineering workflows: Sandboxes and dev environments, Automated verification and guardrails, Feedback loops that keep quality up as output scales.
Build golden paths - repo to production without a human bottleneck
Use Claude / Codex / AI copilots as default tools - not optional helpers
Debug production issues across the stack (no handoffs)
Ship fast, learn fast, fix fast
Take responsibility for what you build - including after it's live

We're backed by tier-1 global VCs, led by second-time founders, and moving fast because the problem demands it. There are no silos here. No "that's not my area." If it ships, you own it.
We're hiring a full-stack software engineer who wants end-to-end ownership - backend, frontend, infrastructure touchpoints, and AI-driven workflows.
If you're looking for narrow scope or strict boundaries, this is not the role. If you like building real systems and taking responsibility for outcomes, read on.
What you'll do:
Own features end-to-end - backend, frontend, APIs, and behavior in production
Build AI-native workflows:
Agent-driven actions
Human-in-the-loop interfaces
Explainability and control surfaces
Use Claude / Codex / AI copilots as default tools - not optional helpers
Work directly with product and customers to refine behavior
Debug production issues across the stack (no handoffs)
Ship fast, learn fast, fix fast
Take responsibility for what you build - including after it's live

We're backed by tier-1 global VCs, led by second-time founders, and already deployed with organizations operating at serious scale. AI is not a feature here - it's the system.
We're hiring a Senior AI Engineer to design, fine-tune, and operate AI agents and large-scale models in production. This role exists because off-the-shelf models aren't enough for the problems we're solving.
If you enjoy pushing models until they break - and then fixing them - keep reading.
What you'll do:
Design and operate AI agents that reason, act, and collaborate with humans
Fine-tune and adapt large language models for:
Behavior analysis
Reasoning over long, messy timelines
High-precision enterprise workflows
Build agent orchestration systems (tool use, memory, planning, feedback loops)
Run large-scale inference and training pipelines in production
Work on model evaluation, drift detection, and continuous improvement
Optimize for latency, cost, and reliability at real enterprise scale
Partner closely with DevOps, security, and backend engineers - no research silos
Ship models that are auditable, explainable, and safe in sensitive environments

Were seeking a Senior Machine Learning Engineer with strong MLOps abilities to own the production ML systems behind user engagement, cardiovascular risk stratification, and personalized health recommendations in the app. You'll build and run the CI/CD, real-time serving, versioning, and monitoring infrastructure that models depend on, working closely with data scientists who own the modeling to make sure what they build runs reliably at scale. You should have a proven track record of shipping ML systems to production and be comfortable using AI coding assistants as a core part of your workflow.
Responsibilities:
Build and own production ML infrastructure, including CI/CD pipelines, real-time model serving, model versioning and registries, automated evaluation pipelines, monitoring, and observability.
Serve models in real time at scale, with a strong focus on low-latency inference, reliability, and graceful degradation under load, and operate batch inference with clear standards for latency, availability, correctness, and cost.
Write high-quality, maintainable, well-tested production-grade code, and own its observability, debugging, reliability, and scalability in production.
Implement model monitoring for drift, data quality, latency, and performance degradation, with automated retraining.

Were seeking a talented and impact-driven Senior Data Analyst, Product to join our ML team. In this role, you will shape the future of the digital health products that help people understand and improve their heart health. By applying your technical skills, analytical mindset, and product intuition to rich real-world health and behavioral data, you will help define the experiences we build for our users and the value we deliver to employers and health plans.
You will collaborate with a wide range of cross-functional partners across Product, Engineering, Data Science, Data Engineering, Clinical, Marketing, and Customer Success. You will use data and analysis to identify and solve our biggest product challenges, influence product strategy and investment decisions, and translate insights into digital solutions that improve the well-being of the people we serve.
What you'll do:
Product leadership: Use data to shape product development, quantify new opportunities, and identify upcoming challenges. Help your partner teams prioritize what to build, set goals, and understand their product's ecosystem, ensuring what we build brings real value to users, clients, and us.
Analytics: Guide teams with data and insights. Develop hypotheses and test them using a varied toolkit of rigorous analytical approaches, from experimentation to causal inference and statistical modeling.
Communication and influence: Don't just present data, tell data-driven stories. Influence partners with clear insights and recommendations, and become a trusted strategic partner through structure and clarity.
Your responsibilities:
Work with large and complex datasets, applying statistical analysis and visualization methods to extract meaningful patterns and trends.
Identify and measure the success of product efforts through goal setting, forecasting, and monitoring of key product and engagement metrics.
Design, execute, and analyze A/B tests, including tests of ML-driven features, accounting for cause/effect and treatment/prevention relationships.
Monitor and analyze the performance of our ML models in production, and generate insights and research leads for model improvements and new data-driven solutions.
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
Partner with Product, Engineering, Data Science, and healthcare professionals to inform and execute product strategy.
Integrate AI tools into your workflows to drive measurable gains in efficiency and quality.
Stay current with the latest research and best practices in healthcare analytics and AI.

Required Data Scientist
Tel Aviv
Full-Time
About Us:
Were building the first AI-native autonomous revenue engine for D2C brands, a new category of AI infrastructure replacing the entire revenue stack.
If you want to build category-defining infrastructure with a team that ships weekly, lets talk.
About the Role:
As a Data Scientist, youll be at the heart of the intelligence behind our product. Youll develop predictive models, analyze complex behavioral datasets, and collaborate across engineering and product to turn insights into real-time actions for our clients. This is a hands-on role with plenty of ownership and room to grow.
Responsibilities
Model Development:
Design scalable ML models that predict customer churn, ideal purchase timing, product recommendations, and more.
Data Exploration & Feature Engineering:
Structure and clean large datasets, develop features, and surface key behavioral patterns.
Collaborate with Engineering:
Work closely with developers to implement models and ensure performance at scale.
Business Insight Generation:
Turn data into actionable insights that drive product features and client decisions.

Required Founding Engineer
Tel Aviv
Full-Time
About Us:
Were building the first AI-native autonomous revenue engine for D2C brands, a new category of AI infrastructure replacing the entire revenue stack.
If you want to build category-defining infrastructure with a team that ships weekly, lets talk.
About the Role:
This is a broad, hands-on engineering role.
Youll work directly with the founders and own the most challenging parts of the platform end to end.
The focus is backend and infrastructure, but youll work across the full stack whenever a problem calls for it.
Youll help shape the technical direction, and how engineering works as the team grows.
Responsibilities:
Own the Challenging Problems - Take the most complex parts of the platform end to end, from architecture through production.
Shape Architectural Decisions - Help define service boundaries, data models, and technical direction as the platform scales.
Build the Core - Design and ship the systems at the heart of the platform.
Scale the Data Pipeline - Build the ingestion, processing, and orchestration layers that move data through the platform reliably.
Own Infrastructure - Shape deployment, observability, and reliability across cloud infrastructure and Kubernetes.
Build End to End - Work across the full stack when the problem calls for it, including the surfaces your services power.

Required Founding ML Engineer
Tel Aviv
Full-Time
About Us:
Were building the first AI-native autonomous revenue engine for D2C brands, a new category of AI infrastructure replacing the entire revenue stack.
If you want to build category-defining infrastructure with a team that ships weekly, lets talk.
About the Role:
Youll build the platform our data science team works on.
That means the pipelines, tooling, and infrastructure that let data scientists train, deploy, and monitor models without needing an engineer at every step - and working alongside them to get their models onto the platform when they do.
The work is predictive ML: churn, purchase timing, and recommendations, running for enterprise clients at scale.
Youll help shape how ML is built and operated here as the team grows.
Responsibilities:
Build the ML Platform - Design the pipelines, tooling, and infrastructure the data science team builds on.
Enable Self-Service - Make it possible for data scientists to train, deploy, and monitor models without an engineer in the loop.
Implement Models on the Platform - Work alongside data scientists to take their models from notebook to production.
Own Features at Scale - Build the feature pipelines that keep training and inference consistent.
Keep Models Healthy - Build the monitoring and retraining that keep predictions accurate over time.
Shape How We Build ML - Help define the tooling, standards, and practices for ML as the team grows.