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As a Drivers & Virtualization Engineer, you will own the host-facing software boundary. Your mission is to ensure our hardware is accessible, secure, and performant across diverse environments-ranging from bare-metal deployments to complex virtualized and multi-device cloud infrastructures. You will focus on building robust kernel-level interfaces where correctness, isolation, and long-term operational safety are paramount.

Responsibilities
Develop and maintain high-performance Linux kernel drivers for proprietary accelerator.

Implement communication protocols and virtual device interfaces to bridge hardware and software.

Manage low-level hardware interactions including PCIe, DMA, MMIO, and interrupt handling.

Enable seamless virtualized access to accelerators using QEMU and KVM.

Design and implement robust device sharing, passthrough, and isolation mechanisms.

Ensure the security of accelerator operations through strict memory protection and resource isolation.

Debug complex failures that span the entire stack: from hardware and kernel to hypervisor and guest OS.

Support the scaling of our architecture from single-device setups to large-scale multi-device deployments.

Were looking for an enthusiastic and highly motivated Technical Support Engineer to identify, diagnose and resolve customers issues. The Technical Support Engineer will be a part of our Professional Services team.

This is an exciting opportunity to work in a challenging, fast-paced environment in a high-performance team. Here we truly put our people first. We strongly believe in teamwork, and we encourage and trust our people to reach higher, learn more, and live up to their potential.


Job Description
Taking ownership of customer issues reported by customers and prioritizing them based on urgency and importance.
Researching, diagnosing, troubleshooting issues and identifying solutions to resolve system issues.
Coordinating support case resolution with the appropriate internal teams: Sales, Professional Services, Product.
Following standard procedures for proper escalation of critical or unresolved issues.

We are looking for an AI-first Software Engineer who is highly product-oriented and excited about building customer-facing systems using modern AI tooling to dramatically increase development speed and operational automation.
What youll do?
Build and ship end-to-end product features (backend, frontend, integrations, automation).
Use AI tools and build the AI infrastructure to accelerate development through scalable workflows, including multi-agent approaches.
Build AI agents that fully automate customer-facing sales and service flows, in a business with a massive volume of textual interactions.

A growing B2B SaaS company is looking for an experienced Head of Data Science to lead its Data Science function and drive the next generation of AI and machine learning capabilities.

This is a strategic leadership role combining people management, hands-on problem-solving, cross-functional collaboration, and ownership of data-driven innovation across the organization.

Responsibilities

Lead and mentor a global team of Data Scientists.

Define and execute the company's Data Science strategy.

Drive the development of advanced machine learning, optimization, and forecasting solutions.

Partner closely with Product, Engineering, Customer Success, and executive leadership.

Translate complex business challenges into scalable analytical solutions.

Support customer-facing initiatives and strategic engagements when needed.

Establish best practices for experimentation, model evaluation, and performance measurement.

Act as a key stakeholder in shaping the company's AI vision and roadmap.

we are looking for a Predictive Analytics Solution Engineer.
Typical Tasks:
Guide and assist customers in utilizing the platform and implementing AI models.
-Help customers understand complex AI concepts, identify relevant use cases, and implement solutions to drive business value.
Address and resolve technical and data-related issues.
Provide valuable feedback to the product team and collaborate to enhance the product.
Analyze model outputs and explain complex ideas in a clear, understandable manner.
Serve as the primary data and technical contact for clients, understanding and addressing their needs.

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.

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 Solution Engineer.
Responsibilities:
Lead and support customer-facing Demand Forecasting use cases from discovery through deployment
Work hands-on with customer data to design, test, and validate forecasting solutions
Act as a trusted analytical and technical advisor to customers, deeply understanding their business context and datasets
Analyze and explain model outputs and complex analytical concepts in a clear, business-oriented way
Troubleshoot technical and data-related challenges and drive them to resolution
Collaborate closely with Data Science and Customer Success teams, providing structured feedback from customer use cases
Help customers achieve measurable business impact and adoption of Demand Forecasting module

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

we are looking for a Senior ML Engineer.
Responsibilities:
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.

we are looking for a Customer-Facing Data Scientist.
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

We are looking for a Senior AI Researcher to join our foundation models team and help advance large-scale models for single-cell RNA (scRNA) data.

In this role, you will focus on training and improving transformer-based and deep learning models, developing algorithmic solutions to challenging modeling problems, and adapting modern foundation model techniques to biological data. This is a hands-on research position for someone who enjoys building and training deep models, understanding their behavior, and pushing them to perform better.

You do not need prior biology experience - but you should be excited to apply your deep learning expertise to a new scientific domain.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Develop, train, and refine transformer-based and related architectures for large-scale scRNA data.
Tackle challenging modeling problems with thoughtful, principled approaches.
Apply ideas from NLP and vision (pretraining, self-supervision, transfer learning) to biological data.
Plan careful experiments, perform ablations, and deeply analyze results to guide model improvements.
Engage directly with large, noisy biological datasets and build intuition for model behavior in this setting.
Partner with engineers, data scientists, and biology experts to turn research ideas into working systems.

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.

Location: Ramat Gan (Bursa area), Israel - Hybrid model

What will you do?

Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.