דרושים » הנדסה » Staff Software Engineer

We're seeking an exceptional Senior Big Data & Machine Learning Engineer who will architect the future of our AI systems and drive technological innovation within our high-performing team.
What you'll be doing
As a key member of our AI team, you will:
Design Scalable Architecture - Architect, implement, and optimize robust ML pipelines that handle massive datasets with elegance and efficiency, from collection through preprocessing to production deployment
Pioneer Technical Solutions - Apply state-of-the-art machine learning technologies to solve complex challenges while maintaining the agility to incorporate emerging innovations
Drive Cross-Functional Excellence - Collaborate strategically with data scientists, software engineers, architects, and product leaders to transform advanced ML solutions into production-ready systems

Were looking for an experienced Software Engineer to join our Data team.
In this key role, you will develop our data platform, working on cloud-based microservices data pipelines. As we are building the company data platform, it has direct impact on our customers and also enabled many of the other groups in the organization. You will also be responsible for building microservices that need to work on big data scale (about 250K records/sec) in a law latency as part of a dynamic team.
Key Responsibilities:
End-to-end development of company massive data infrastructures and services.
Researching new technologies and adapting them for use in the companys product
Working closely with the product, DevOps, and security teams.

We are on the search for a Senior Machine Learning Engineer who will join our Data team in Tel Aviv. As a Senior ML Engineer in a Data-Driven company, you will have a significant opportunity for impact. You will be part of the team that turns data into solutions that influence the product and drive strategic business decisions that shape the direction of the company.
Here are a few of the things you will do:
Own the end‑to‑end ML lifecycle: design, build, and operate data ingestion, feature‑store, training, evaluation, CI/CD, and low‑latency serving pipelines that power AI experienceslead qualification, generative content, conversational assistance, and more.
Collaborate deeply with AI researchers, engineering managers, and product managers to transform product ideas into reliable, scalable ML systems, iterating quickly from prototype to production.
Advance our MLOps platform by developing orchestrations, model registries, automated monitoring, and retraining workflows that enable shipment of AI features autonomously and safely.
Elevate engineering culture through code reviews, documentation, mentorship, and promoting experimentation and data‑driven decision making.

We seek an experienced Software Engineer with a strong background to become an integral member of our Data-Core team, tasked with the mission of processing, structuring, and analyzing hundreds of millions of data sources.
Your role will be pivotal in creating a unified, up-to-date, and accurate utilities map, services, and applications for accelerating our mapping operations. Your contributions will directly impact our core product's success.
Responsibilities:
Collaborate with cross-functional teams to design, build, and maintain data processing pipelines while contributing to our common codebase.
Contribute to designing and implementing data architecture, ensuring effective data storage and retrieval.
Develop and optimize complex Python-based applications and services to allow more efficient data processing and orchestration, enhancing the quality and accuracy of our datasets.
Implement geospatial data processing techniques and contribute to the creation of our unified utilities map, enhancing the product's geospatial features.
Drive the scalability and performance optimization of data systems, addressing infrastructure challenges as data volume and complexity grow.
Create and manage data infrastructure components, including ETL workflows, data warehouses and databases, supporting seamless data flow and accessibility.
Design and implement CI/CD processes for data processing, model training, releasing, testing and monitoring, ensuring robustness and consistency.

As a Platform Team Lead at our company, you will lead a critical cross-functional team focused on building and evolving the core infrastructure that powers our Big Data, Marketing Tech, CRM, and Data Science initiatives.
You will drive technical strategy, mentor engineers, and work closely with R&D, Product, and Data Science teams to deliver high-performance, scalable, and innovative platform solutions.
What You'll Be Doing
Lead and grow a high-performing platform engineering team.
Design, develop, and maintain scalable backend systems, ensuring stability, performance, and operational excellence.
Build core services and infrastructure that enable Marketing, Data Science, CRM, and Engineering teams to move faster and smarter.
Drive platform initiatives around Big Data processing, event-driven architectures, and distributed systems.
Partner with stakeholders across the company to understand evolving business needs and translate them into technical solutions.
Champion innovation by evaluating and integrating new technologies, frameworks, and practices that elevate our product and internal capabilities.
Maintain a high bar for code quality, security, and scalability.
Provide hands-on technical leadership guiding design, code reviews, and system architecture discussions.
Foster a culture of learning, collaboration, and continuous improvement.

we are looking for an outstanding and passionate full stack developer to join our team where you'll have the opportunity of:
True Full-Stack Ownership - Design, build, test, deploy and innovate across the entire technical stack.
Startup Energy, Enterprise Resources - Enjoy the nimble culture of a startup backed by global infrastructure.
Boundless Growth Potential - Thrive in a flat organizational structure where impact is king.
End-to-End Involvement - Participate in the full product lifecycle from concept to delivery
What you'll be doing:
Design, develop, and maintain scalable backend systems, written in Go, Ts & Python
Build and optimize data processing pipelines for large datasets using databricks
Contribute to architectural decisions and technology selection
Translate complex business requirements into technical implementations that create measurable value

architecting a new approach to the enterprise data stack built for the age of reasoning. The Data Platform sets the standard for agentic AI data infrastructure with a cloud and AI-native software solution that can be deployed anywhere. It transforms legacy data silos into data pipelines that dramatically increase GPU utilization and make AI model training and inference, machine learning, and other compute-intensive workloads run faster, work more efficiently, and consume less energy.

a pre-IPO, growth-stage company on a hyper-growth trajectory. Weve raised $375M in capital with dozens of world-class venture capital and strategic investors. We help the worlds largest and most innovative enterprises and research organizations, including 12 of the Fortune 50, achieve discoveries, insights, and business outcomes faster and more sustainably. Were passionate about solving our customers most complex data challenges to accelerate intelligent innovation and business value. If you share our passion, we invite you to join us on this exciting journey

What you'll be doing:

The filesystem group is a high-powered team responsible for implementing algorithms at scales of 100s of PBs. The team also manages the core filesystem components, including blocks and metadata management, snapshots, RAID logic, object-store tiering, unique cloud disaster recovery features, and more. And most importantly, they skillfully handle the most delicate part of the solution our customers data.
As a Senior Software Engineer, youll:
Design and develop distributed file system components to support data management features such as snapshots, replication, tiering, and advanced data reduction algorithms;
Participate in the design, architecture, and implementation of next-generation storage architecture;
Assist in technically managing initial storage implementations including proofs-of-concept;
Diagnose bottlenecks and implement clean and performant solutions to achieve unbeatable performance;
Design algorithms and data structures to make sure customer data is safe and coherent across our solution in a wide variety of failure modes; and
Constantly revisit the architecture, algorithms, and methodologies to improve productivity, reliability, and maintainability.

Were growing and looking to hire a Data Team Leader who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity.
We are seeking a Data Team Leader with strong technical expertise and a flair for innovation to join our dynamic Data Science and Analytics group. You will play a key role in advancing solution by crafting and sustaining the data collection infrastructures, including cutting-edge LLM data pipelines and web collection frameworks, along with data alliances.
This role requires a visionary leader who is both hands-on and proactive, able to collaborate closely with analysts, data scientists, and product teams to devise scalable solutions. Your mission will be to ensure data reliability and to drive the creation and maintenance of high-scale data collection systems, manage data alliances, and uphold governance within our data collection infrastructure.
Responsibilities:
As Data Team Leader, Your impact will be:
Leading and scaling a team of talented LLM engineers, network analysts, and web scrapers to drive core data initiatives.
Fostering a culture of innovationpromoting continuous learning and high engineering standards.
Defining data collection strategies aligned with business KPIs and ensuring measurable impact.
Maintaining and evolving our data infrastructure, with a strong focus on automation and efficiency.
Working closely with backend developers, PMs, data scientists, analysts, and external data partners to design and deliver robust data solutions.
Integrating and managing data flows across various sources and systems.
Taking ownership of data alliances, budgets, and overall data strategy.

JR295989

As a Backend Software Engineering, your job responsibilities will include:

Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.

Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.

Make design decisions on the basis of performance, scalability, and future expansion.

Work in a Hybrid Engineering model and contribute to all phases of SDLC including design, implementation, code reviews, automation, and testing of the features.

Build efficient components/algorithms on a microservice multi-tenant SaaS cloud environment.

Code review, mentoring junior engineers, and providing technical guidance to the team (depending on the seniority level).

We are looking for a Data Engineer.
The Data Engineer position is a central role in the Tech Org. The Data Engineering (DE) team is a Change Agent Team that plays a significant role in the ongoing (at advanced stages) migration to cloud technologies. The ideal candidate is a senior data engineer with a strong technical background in data infrastructure, data architecture design and robust data pipes building. The candidate must also have collaborative abilities to interact effectively with Product managers, Data scientists, Onboarding engineers, and Support staff.
Responsibilities:
Deploy and maintain critical data pipelines in production.
Drive strategic technological initiatives and long-term plans from initial exploration and POC to going live in a hectic production environment.
Design infrastructural data services, coordinating with the Architecture team, R&D teams, Data Scientists, and product managers to build scalable data solutions.
Work in Agile process with Product Managers and other tech teams.
End-to-end responsibility for the development of data crunching and manipulation processes within the product.
Design and implement data pipelines and data marts.
Create data tools for various teams (e.g., onboarding teams) that assist them in building, testing, and optimizing the delivery of the product.
Explore and implement new data technologies to support data infrastructure.
Work closely with the core data science team to implement and maintain ML features and tools.