דרושים » תוכנה » Senior Software Engineer

If youre looking to build something big, solve real problems, and grow fast-wed love to meet you.

Responsibilities:

Own, enhance, and improve core platform

Build and maintain systems for collecting and processing metrics from client environments

Focus on system efficiency and resilient infrastructure

Integrate well-known SaaS platforms into big data repository (e.g., major cloud providers, Datadog, Snowflake)

Optimize Spark and Airflow processes

Contribute to data design and platform architecture while working closely with other business units and engineering teams

Face the challenges of testing and monitoring large-scale data pipelines

Responsibilities:

Own, enhance, and improve our core platform.

Focus on system efficiency and resilient infrastructure.

Integrate well-known SAAS platforms to our big data repository e.g., the major cloud providers, DataDog, and Snowflake.

Optimize Spark and airflow processes.

Contribute to data design and platform architecture while working closely with other business units and engineering teams.

Face the challenges of testing and monitoring your large-scale data pipelines.

If youre looking to build something big, solve real problems, and grow fast-wed love to meet you.

Responsibilities:

Own, enhance, and improve core platform

Focus on system efficiency and resilient infrastructure

Integrate well-known SAAS platforms to big data repository e.g., the major cloud providers, DataDog, and Snowflake

Optimize Spark and airflow processes

Contribute to data design and platform architecture while working closely with other business units and engineering teams

Face the challenges of testing and monitoring your large-scale data pipelines

Required Senior Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Senior Algo Data Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

Were looking for a Senior Software Engineer to join our growing R&D team. In this role, you will play a critical part in designing, building, and optimizing complex systems that power our AI-driven platform. Youll work across the stack- primarily on backend services - with opportunities to influence architectural decisions and build highly scalable and performant systems. Youll collaborate closely with AI, product, and frontend teams to bring advanced features to life and ensure a seamless, intelligent experience for our users.

This is a high-impact role for someone who is passionate about engineering excellence, eager to shape systems end-to-end, and ready to grow with a fast-moving, AI-first company.

Key Responsibilities:
Design, develop, and maintain robust backend systems and services.
Ensure the scalability, performance, and security of backend components.
Collaborate with front-end developers and data teams to integrate user-facing elements with server-side logic.
Optimize the platform's infrastructure to handle large-scale data processing and analysis.
Troubleshoot and debug complex issues, identifying and implementing the most effective solutions.
Contribute to the architecture and system design decisions for the backend infrastructure.
Stay up to date with industry trends and new technologies to continuously improve backend performance.

We are looking for a highly skilled and motivated Senior II Software Engineer to join the Operational Experience engineering team. The team is part of the Customer Experience group, which is responsible for the platform, tools, and customer-facing experiences that power how our customers interact with our ecosystem. This is a high-impact, hands-on role, in which youll be working closely with product managers, designers, customer-facing teams, and engineering partners across the company.

You will operate at the intersection of backend engineering, data-intensive systems, platform development, and customer experience. The ideal candidate brings strong expertise in Node.js and TypeScript, along with deep experience working with large-scale data stores, event-driven pipelines, data models, and high-throughput infrastructure. You will work closely with cross-functional partners to design and implement robust backend services, data-access patterns, and operational workflows that power the portal and internal tools. As we invest heavily in Agentic AI, you will also play a central role in shaping and implementing AI-driven capabilities across the platform. While the role is primarily backend, you will occasionally contribute across the full stack when it supports end-to-end delivery.

If you enjoy owning complex problems end to end, improving systems at scale, and building experiences that bring real value to customers, we would love to meet you.

What you'll be doing:
Drive technical direction and architecture within the OX team and across the broader CX organization. You will proactively identify opportunities to improve performance, resilience, cost, scalability, and developer experience, primarily in backend systems but with influence across the stack.
Lead the development of AI-driven and Agentic AI capabilities. Define how LLMs integrate into our platform, build AI-powered workflows, and establish strong engineering patterns for safe and reliable adoption.
Own and evolve the data foundations behind the portal. Optimize pipelines, improve data quality and freshness, and design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, MySQL, and related systems.
Work closely with product, design, customer-facing teams, and partner engineering groups. Turn ambiguous problems into clear execution plans and ensure alignment with customer and business goals.
Shape shared standards and platform best practices. Guide other teams on backend services, data integration patterns, portal development approaches, and AI-enabled workflows.
Mentor and elevate engineers across the CX group. Promote engineering excellence, share knowledge openly, and help teams adopt effective modern development practices.
Own delivery of high-impact initiatives. Contribute hands-on when needed, remove blockers, maintain execution momentum, and drive projects from concept to production.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.


What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across our decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

Were looking for a talented and experienced Senior Software Engineer to join the CMA Platform Team - the team building the core platform and shared services that power how our company developers build and ship products.
In this role, youll design and develop scalable platform capabilities and internal solutions that will be used by engineering teams across our company. From authentication and RBAC to cross-cutting services and developer-facing APIs, your work will be at the heart of our companys management and control plane, enabling other teams to move faster, safer, and with greater consistency.
Youll work on backend services, integration patterns, and platform abstractions that provide a solid, secure, and observable foundation for dozens of products and features.
Responsibilities:
Design, build, and maintain core CMA platform services used by multiple product teams (e.g., authentication, RBAC, account lifecycle, shared configuration, and more).
Develop scalable, resilient microservices that operate in near real-time and support high-throughput, global production environments.
Provide clear, well-documented APIs and SDKs that improve developer experience and make platform capabilities easy to adopt.
Collaborate closely with other engineering teams to understand their needs and translate them into reusable platform features and best practices.
Own services end-to-end: design, implementation, testing, deployment, monitoring, and continuous improvement.
Drive technical excellence in the platforms architecture, including reliability, security, observability, and performance.
Evaluate and integrate third-party technologies where it makes sense to accelerate the platform roadmap.

Required Senior Machine Learning Engineer I - GenAI Applications
20031
Leadership/Team Quote:
This opening is for the GenAI Infra team in the Marketplace AI department.
The GenAI Infra team builds the Agents platform which is used for all agnetic and non-agentic flows. This team is responsible for both the GenAI agents and the orchestration around them, helping support applications such as the AI Trip Planner, Free text search, etc.
Role Description:
As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.