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Were looking for an Account Manager who will manage a portfolio of our strategic customers in Israel from the onboarding stage to assuring satisfaction while identifying business needs in the customers AWS environment.
Work location: hybrid from Tel Aviv
Curious about what it's really like to work?
Explore our benefits, culture, and what success in your first year could look like here.
If you are interested in this opportunity, please submit your CV in English.
Key Responsibilities
Identify Cost Optimization, upsell, cross-sell, and renewal opportunities, and the need for a Dedicated DevOps or FinOps service.
Oversee a portfolio of assigned customers, develop new business from existing clients, and meet sales goals.
Onboard new customers and guide them through onboarding, ensuring a smooth transition to our product or service. Provide training and resources to help them get started effectively.
Act as the primary point of contact for assigned customer accounts. Develop a deep understanding of their business needs and objectives, and proactively engage with them to understand their evolving needs, challenges, and goals.
Gather feedback from customers regarding their experiences and needs. Relay this feedback to internal teams for continuous improvement.
Encourage satisfied customers to become advocates by participating in case studies, testimonials, or referrals.
Maintain and develop strategic vendor relations with AWS.
Regularly attend business events and conferences to promote and educate prospective clients on our benefits.

We seek an Account Executive to drive our business growth in the Israeli territory, focusing on Greenfield accounts while delivering an outstanding customer experience. You will own the full sales cycle, from prospecting to close, and act as a trusted advisor connecting high-growth startups with the DevOps, FinOps, and GenAI expertise they need to scale.
Work location: hybrid from Tel Aviv
Curious about what it's really like to work?
Explore our benefits, culture, and what success in your first year could look like here.
If you are interested in this opportunity, please submit your CV in English.
Key Responsibilities
Develop and execute targeted territory plans to achieve or exceed revenue, growth, and margin targets
Manage all phases of the business development cycle, including proposal negotiations, statements of work (SoWs), and contract finalization
Prospect new customers and communicate regularly with AWS representatives to co-sell and identify joint opportunities
Maintain and grow strategic vendor relationships with AWS
Articulate our value proposition and competitive differentiation to technical and business stakeholders
Attend industry events and meetups to promote our and educate prospective clients
Collaborate cross-functionally with Marketing, Operations, Delivery, and Solutions Architects
Leverage AI-powered sales tools to research prospects, personalize outreach, and derive actionable pipeline insights
Commit to regular business travel, locally and internationally

We are looking for a detail-oriented and motivated Bookkeeper to join our Finance team.

This is an excellent opportunity to gain hands-on experience, develop professionally, and become part of a dynamic company operating at the intersection of technology, data, and creative.

Responsibilities
What Youll Be Doing
Process and record supplier and customer invoices accurately and on time.
Perform bank and credit card reconciliations.
Support accounts payable and accounts receivable processes.
Maintain accurate financial records and documentation.
Work closely with internal teams, suppliers, and customers.
Support the Finance team with ongoing financial and administrative tasks.

As a Staff Software Engineer, you will serve as a technical authority and play a pivotal role in scaling our core platform. Your focus will span architecture, security research, and engineering excellence:

Lead & Architect: Design, build, and scale high-performance software while driving architectural best practices across the R&D organization.
Security & AI Innovation: Drive deep-dive research into cloud, SaaS ecosystems, and AI agents to build proactive detection models, mitigation strategies, and threat intelligence.
Engineering Excellence: Elevate code quality, testing standards, system monitoring, and documentation across teams.
Cross-Functional Ownership: Partner closely with Product and R&D to translate complex security requirements into scalable technical solutions.
Scale & Optimize: Identify and resolve systemic performance bottlenecks and architectural challenges.
Mentorship & Leadership: Act as a technical mentor, driving engineering standards and fostering a strong knowledge-sharing culture.

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.

Were looking for a highly motivated, data-driven Senior Retargeting campaign Manager to lead user re-engagement strategies across a growing portfolio of clients. In this role, youll combine data, audience insights, creative strategy, and AI-driven optimization to improve campaign performance, increase LTV, and drive strong results. Youll also lead cross-team initiatives to improve and scale our retargeting products and technology.

Key Responsibilities
Retargeting Campaign Management: performance monitoring, budget allocation, targeting, high-volume mobile native retargeting advertisers, ensuring optimal return on ad spend (ROAS).
Cross-Functional ownership: Lead 1 or more strategic cross-department projects, collaborating across teams to enhance company-wide marketing capabilities and technology.
Audience & Campaign Optimization: Analyze complex audience segments on an ongoing basis to build hyper-targeted re-engagement strategies; continuously optimize pre- and post-install/event metrics using proprietary tools, and dashboards.
AI & Automation Innovation: Leverage a proven track record of implementing AI toolsets and machine learning frameworks for campaign management and creative optimization.
Product & Data Science Collaboration: Partner with product, data science, and engineering teams to extract deeper campaign insights, refine predictive modeling, and improve internal retargeting infrastructure.
Strategic Client Alignment: Translate performance data into actionable growth strategies, delivering high-level insights and recommendations to client-facing teams.

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.

As a Senior Account Manager, you'll own a portfolio of our top strategic clients end-to-end - from onboarding through QBRs and growth planning. You'll drive upsells, uncover expansion opportunities, and turn account insight into revenue, working alongside our global Growth team (US, EMEA, APAC) and closely with Product, Sales, and BI.

This is a senior role with real scope: you'll own the highest-value accounts in the book, set the playbook other CSMs follow, and have a direct line to shaping how the Growth org scales.

Responsibilities:
Revenue Growth - Grow and scale strategic client budgets through upsell and cross-sell.
Client Communication - Build long-term client relationships through proactive, high-value engagement and in-person visits.
Collaboration - Partner with product and sales to align on client needs and growth opportunities.
Strategic Leadership - Drive cross-team initiatives using AI and data to shape client strategy.
Reporting & Analysis - Turn performance data into insights that drive client decisions.
Team Standards - Build and scale playbooks that raise the bar for account management.

Required Senior Data Engineer
About the role:
You will specialize in designing and building world class, scalable data architectures, ensuring reliable data flow and integration for groundbreaking biotechnological research. Your expertise in big data tools and pipelines will accelerate our ability to derive actionable insights from complex datasets, driving innovations in improving patients outcome and in delivering life savings treatment solutions.
In this role, you will work closely with data scientists, AI/ML engineers, architect and other cross-functional teams to understand their data needs and requirements. You will also be responsible for ensuring that data is easily accessible and can be used to support data-driven decision making.
Location: Ramat Gan, (Hybrid model)
What will you do?
Design, build, and maintain data pipelines that ingest, transform, and load noisy, heterogeneous biological data at scale - from single-cell sequencing, genomic, and clinical sources - across databases, APIs, and flat files
Enhance our data warehouse system to dynamically support multiple analytics use cases
Implement and productize complex scientific and computational algorithms as scalable, production-grade pipeline components
Drive our data infrastructure toward becoming AI-native, enabling AI/ML systems and agents to reliably query, reason over, and act on our data
Implement data governance policies and procedures to ensure data quality, security, and privacy
Collaborate with ML and AI scientists and other cross-functional teams to understand their data needs and requirements
Drive team capability growth by championing an AI-first SDLC, mentoring data engineers on AI-assisted development practices and tooling
Develop and maintain documentation for data pipelines, processes, and systems
Requirements
We will only consider senior data engineers that have demonstrated strong system design skills combined with an extensive background working with data orchestration, data warehousing and ETL tools.

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.