

You will be responsible for creation of concept, design, development, testing and maintenance of applications for reliability, security, manageability, scalability, extensibility, performance, and re-use; provides technical expertise in the areas of architecture, design, and implementation. Works with technical and business team members to create excellent software. You will help determine the best implementation that will meet the design of the Application Architect. Ensures that thorough unit and component testing is carried out. Sets and adheres to software coding and style guides to ensure consistency.
What you will accomplish:
What you will bring:
משרות נוספות שיכולות לעניין אותך

What you will accomplish:
What you will bring:

This person will need to work with a large number of teams within eBay to make these visions successful, so building close, effective relationships with partner Product Managers will be critical. In addition, this person will translate product strategy into detailed specifications, make functional and user interface design tradeoffs, manage product launches and own the product successes post-launch. Having the experience and ability to write clear, consistent and detailed product specs will be essential. He or she will work closely with a cross-functional team of engineering, analytics, product marketing, and user research to deliver these products.
Job Requirements:
Basic Qualifications:

Responsibilities:
Analyze eBay’s large and rich datasets, drive insights from data to diagnose the root cause behind trends and ultimately improve our user experience.
Build machine-learning models to predict user behaviors and infer marketing performance, support business decisions through trusted and well-defined model results.
Measure and optimize ongoing performance for marketing activities based on data-driven insights, understand key drivers and identify new marketing opportunities by focusing on bankable metrics. Deep-dive into campaign performance and provide insights into what is working and why
Mine data to optimize marketing campaigns, revenue growth, and customer experiences. Perform customer segmentation to understand target audiences better.
Develop strategies for channel optimization and content strategy.
Design, develop, and execute experimentation frameworks, including A/B testing and uplift modeling, to measure marketing effectiveness.
Develop and implement solutions for Marketing Mix Modeling (MMM) and Marketing Attribution (MTA).
Provide data support for business operation, design self-service tools, dashboards etc.
Communicate business performance in a clear and insightful way to the business.
Develop, improve and systemize crisp & accurate reporting. Streamline processes and identify/execute on automation and time-saving opportunities. Leads automation of recurring tasks.
Translates business problems into a scientific formulation for an AI/Analytics Product solution. Defines requirements and collaborates with engineers to build and productionize AI enabled Analytics Products
Job Skills required:
Intellectual curiosity, passion for problem-solving, and comfort with ambiguity.
A passion for understanding and serving the unique community of eBay.
Sound business judgment and quantitative analytic ability.
Strong communication skills and experience presenting complex quantitative analysis into action-oriented recommendations.
Understand a variety of machine-learning techniques (regression, clustering, decision tree learning, etc.) and their real-world advantages/drawbacks.
Effective team player and works well within a team and contributes effectively to the success of those interactions regularly.
Prior experience or deep knowledge of Performance Marketing and/or Brand Marketing will be highly preferred.
Desired Qualifications:
BA/BS in Mathematics, CS, Statistics, Economics, Business, or other related fields.
5+ years hands-on work experience in data analysis, with a focus on onsite web analytics, A/B testing, machine learning and report automation.
Skilled in database query tools utilizing SQL, and Hadoop experience is a plus.
Good Excel and PowerPoint skills, proficiency with statistical analysis tools such as Python or R.
Knowledge of AI tools and techniques, such as Gemini, GPT, LLMs etc.

As a senior engineer, you'll take part throughout the product development lifecycle—from conceptual design to product launch—while working closely with Product Managers, Designers, and Architectural teams.
What you'll do and learn:
Develop features that are modular and loosely coupled
Able to translate product and design documents into clean, high-quality, crash-free, well-tested and maintainable production code autonomously
Write unit tests and automation code for all shipped features
Conduct code review for immediate team
Develop and maintain technical documentation to support software applications.
Propose and evaluate multiple design options, providing estimates for each.
Structure and complete tasks independently, meeting deadlines and milestones.
Effectively communicate assumptions and seek clarification from stakeholders, ensuring alignment and understanding across all domains.
What you will bring:
4+ years professional experience in native mobile development
Understanding of advanced swift features such as generics / concurrency mgmt /
Experience with dependency management tools in iOS - SPM/Cocoapods/Carthage etc
Basic understanding of system design for large scale consumer mobile applications
Familiarity with CI/CD tools
Experience implementing modern platform design patterns
Understanding of testing iOS applications using platform tools
Experience with production monitoring
Basic proficiency with swift memory management
Strong learning ability, self-driven
Excited about new and innovative technologies within immediate field of expertise
Attending knowledge sharing sessions, both within the company and externally
Innovative, team player, excellent communication and decision-making
Bachelor's degree in EE, CS or other related field or equivalent exp.

Architectural Leadership: Own and evolve the architecture for risk engineering systems, ensuring solutions are scalable, secure, maintainable, and in alignment with enterprise standards.
System Design: Eliminate duplication across systems and ensure clear responsibility boundaries; align systems with business needs and future scalability.
Engineering Excellence: Champion clean architecture, promote use of modern frameworks, enforce quality gates, and ensure adherence to design patterns and coding standards.=
Lead by Example: Write reference implementations, contribute to core libraries, and conduct in-depth code reviews to influence standards and uplift team capabilities.
Cost Optimization: Propose and drive engineering solutions that reduce operational overhead, improve resource efficiency, and automate manual processes.
Technical Vision: Set the long-term technical direction for the risk engineering domain, align with enterprise architecture strategies, and ensure teams are building toward a common vision.
Framework Development: Identify opportunities to build reusable components, services, and frameworks that accelerate feature delivery across the organization.
Modernization: Lead migrations of legacy systems into modern architectures and cloud-native paradigms with minimal disruption and high impact.
Collaboration: Drive complex technical discussions, build consensus across engineering, product, and operational teams, and ensure smooth delivery of cross-functional projects.
Documentation & Governance: Create well-structured Architecture Decision Records (ADRs) and contribute to technical documentation and standards.
Mentorship: Act as a technical mentor, guiding senior and junior engineers on architecture best practices and advanced problem-solving.
Introduce AI-first frameworks and reusable components that reduce developer friction and enable faster iteration.
Automate diagnostics, monitoring, and remediation using intelligent assistants and prediction-based alerting.
Shape the next generation of risk systems that are autonomous, scalable, and continuously learning.
Excellent in interpersonal communicatomn
Proven experience (12+ years) in software engineering with significant experience (5+ years) in architecture roles in large-scale, distributed systems.
Strong hands-on experience with:
Languages/Frameworks: Java/Kotlin, JEE, Spring, Spring Boot, Node.js, React.js, Material design, Python,
Messaging & Streaming: Kafka, messaging paradigms (pub-sub, queues)
Databases: RDBMS (e.g., MySQL, PostgreSQL), NoSQL (e.g., MongoDB, Cassandra), distributed cache
Containers & Orchestration: Docker, Kubernetes
Big Data & Stream Processing: Hadop,Apache Flink, Apache Spark
Expertise in building platforms for feature store, Nrt aggregation, online/offline data parity.
Deep understanding of architectural patterns (microservices, event-driven systems, domain-driven design, CQRS).
Experience in driving architecture transformations and migrations.
Exceptional communication, presentation, and consensus-building skills.
Demonstrated ability to influence senior stakeholders and technical teams.
Expert in resolving performance bottlenecks.
Experience in risk or fraud engineering systems.
Strong understanding about cloud-native architectures.
Experience working in large-scale eCommerce or financial transaction systems.
Open source code committer

This is an opportunity to:
Lead and manage a team of applied researchers and engineers with deep expertise in natural language processing, large language models / AI, recommender systems, and ML production engineering
Drive personalization strategy for eBay recommendations and influence look and feel of the eBay homepage
Influence how people will interact with recommender systems in the future, and how recommender systems technology will evolve
Work with unique and large data sets of unstructured multimodal data representing eBay's vast and varied inventory, and millions of users
Develop and deploy state of the art AI models
Deploy big data technology and large scale data pipelines
Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations
Qualifications
MS/PhD in Computer Science or related area with 8 years of relevant work experience (or BS/BA with 10 years) in Engineering / Machine Learning / AI
Experience leading a nimble engineering/research team, preferably in a ML/AI technology environment
Experience with using cloud services, big data pipelines and databases
Experience in Natural Language Processing (NLP) and industrial recommender systems
Experience in production engineering practices and software development in an OO language (Scala, Java, etc.) and high volume traffic webapp development in an industrial setting
Previous publications experience with academic papers, patents/IP, or technical blogs is a plus.
Links to some of our previous work:
(GenAI Agentic Platform)

You will be responsible for creation of concept, design, development, testing and maintenance of applications for reliability, security, manageability, scalability, extensibility, performance, and re-use; provides technical expertise in the areas of architecture, design, and implementation. Works with technical and business team members to create excellent software. You will help determine the best implementation that will meet the design of the Application Architect. Ensures that thorough unit and component testing is carried out. Sets and adheres to software coding and style guides to ensure consistency.
What you will accomplish:
What you will bring:
משרות נוספות שיכולות לעניין אותך