דרושים Ml Engineering Tl/architect T27 ב-איביי ב-India, Bengaluru

• Design, deliver, and optimize high-performance, large-scale applications, data pipelines, and ML service infrastructure with exceptional speed and reliability.
• Enhance core products by skillfully integrating, fine-tuning, and deploying advanced machine learning models for optimal performance and impact.
• Command the full software development lifecycle—from initial design and architecture to coding, testing, deployment, and maintenance—while producing clean, efficient, and documented code.
• Develop and execute sound technical strategies for complex projects, taking into account business goals, timelines, and long-term impact.
• Work closely with product managers and partners to translate business requirements into robust technical solutions, ensuring alignment across teams.
• Take ownership of cross-team engineering efforts and guide junior team members, setting a high standard for technical excellence and professional growth.
• Drive innovation by developing novel solutions to challenging problems and actively contribute to a culture of knowledge sharing by both teaching and learning from others.

• Masters or Bachelors degree in Computer Science or a related field with 10+ years of experience in building large-scale distributed applications and backend services.
• Expert with Java, Kotlin to build server side technologies is required.
• A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design/architecture, and core Statistics knowledge
• Experience in the close examination of data, computation of statistics, and deriving of data insights
• Proven experience designing and operating Big Data processing pipelines (Hadoop, Spark) and working with NoSQL databases or key-value stores (e.g., MongoDB, Redis).
• Hands-on experience with the end-to-end lifecycle of machine learning, including model deployment and application at scale. Experience in AI research or industrial recommendation systems is a significant plus.
• Experience with cloud services and familiarity with Large Language Models (LLMs) or prompt engineering is highly desirable.
• A passion for technical excellence, excellent communication skills, and a “can-do” attitude with a willingness to learn and master new technologies.

• Proven expertise in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, Keras.

• Strong understanding of machine learning fundamentals, algorithms, and model evaluation techniques.

• Hands-on experience with ML Ops tools and best practices.

• Proficiency in working with large scale data in hadoop and spark.

• Proficient with prediction accuracy, latency, throughput, confidence scores, and drift (data & concept).

• 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
  

• Design and build machine learning models to detect fraud, bot attacks, collusion etc.

• Perform feature engineering, model development, evaluation, and optimization for high-accuracy ML applications.

• Fine-tune and implement Deep Neural Network (DNN) architectures.

• Construct robust ML pipelines for training, validation, and deployment using modern ML stacks.

• Apply prompt engineering techniques with Generative AI models (LLMs, diffusion models, etc.) to tackle application-driven problems.

• Leverage vector databases and build/optimize embeddings for search, retrieval, and semantic understanding.

• Lead efforts in simulation, synthetic data generation, and experimentation.

• Build reliable APIs and services that expose ML model outputs for real-time decisioning.

• Evaluate bias and fairness across population subgroups.

• Maintain logging, tracing, and alerting for model inputs/outputs, feature importance, versions, and pipeline steps.

• Lead and participate in data validation, preprocessing, and cleansing workflows to ensure ML readiness.

• Work closely with engineers, product managers, and collaborators to develop scalable ML-powered applications.
  

What will you bring?

• At least 5 years of experience in building AI/ML-based products and solutions in production environments.

• A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design, and core Statistics knowledge

• Proven expertise in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras.

• Deep understanding of machine learning fundamentals, algorithms, and model evaluation techniques.

• Hands-on experience with ML Ops tools and best practices.

• Experience with OCR, NLP, vector search, embeddings, and LLM-based applications.

• Experience in the close examination of data and computation of statistics

• Proficiency in working with large scale data in hadoop and spark.

• Proficient with prediction accuracy, latency, throughput, confidence scores, and drift (data & concept).

• Strong programming, system design, and debugging skills.

• Experience working in domains such as fraud detection, credit risk, compliance, advertising, or recommendations is highly preferred.

• Publication of research papers or technical articles in ML conferences or journals is highly desirable.

This is an opportunity to:

• Influence how people will interact with eBay’s 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, including billions of items and millions of users

• Develop and deploy state-of-the-art AI models to production which have direct measurable impact on eBay buyers

• Deploy big data technology and large scale data pipelines

• Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations

Qualifications:

• MS in Computer Science or related area with 3 years of relevant work experience (or BS/BA with 5 years) in Engineering / Machine Learning / AI

• Experience building large scale distributed applications and expertise in any OO language (Scala, Java, etc.)

• Experience building with no sql databases and key value stores (MongoDB, Redis, etc)

• Generalist with a can do attitude and willingness to learn/pick up new skill sets as needed

• Experience with big data pipelines (Hadoop, Spark) is a plus

• Experience in AI applied research and industrial recommendation systems is a plus

• Experience with Large Language Models (LLMs) and prompt engineering is a plus

Links to some of our previous work:

• (GenAI Agentic Platform)

• Technical Vision & Strategy:

  • Define and drive the long-term technical vision, roadmap, and architecture for the engineering organization.

  • Align engineering strategy with overall business goals and product vision.

  • Evaluate and recommend new technologies, tools, and methodologies.

  • Ensure technical decisions support scalability, reliability, security, and maintainability.

• Team Leadership & Management:

  • Lead, mentor, and grow multiple Engineering Managers and/or Team Leads.

  • Oversee the hiring, onboarding, performance management, and career development of engineering staff (including managers and senior ICs).

  • Foster a high-performing, collaborative, innovative, and inclusive engineering culture.

  • Build and maintain team morale, engagement, and retention.

• Delivery & Execution:

  • Oversee the planning, execution, and timely delivery of complex software projects across multiple teams.

  • Ensure teams adhere to best practices (coding standards, code reviews, testing, CI/CD).

  • Manage engineering budgets, resource allocation, and capacity planning.

  • Track key performance indicators (KPIs) related to delivery velocity, quality, and system health

• Process & Operational Excellence:

  • Establish, optimize, and standardize engineering processes (SDLC, Agile/Scrum/Kanban, release management, incident response).

  • Drive continuous improvement in engineering efficiency, productivity, and quality.

  • Implement and monitor metrics to measure team and organizational performance.

• Cross-Functional Collaboration:

  • Partner closely with Product Management, Design, Data Science, Security, and IT/Operations to define requirements, prioritize work, and ensure successful product delivery.

  • Collaborate with senior leadership (Sr. Directors, other Directors, Executives) on strategic initiatives and company-wide goals.

  • Represent the engineering organization in cross-functional meetings and strategic discussions.

• Technical Oversight & Quality:

  • Provide high-level technical guidance and oversight across projects.

  • Champion software quality, best practices, and operational reliability (e.g., SLOs, SLIs).

  • Ensure systems are designed for scalability, performance, and cost-efficiency.

  • Manage technical debt and advocate for necessary refactoring/infrastructure investments.

• Resource Management:

  • Growing your team through coaching, mentoring

  • Forecast hiring needs and participate in recruitment strategy.

• 10+ years of software engineering experience, with 5+ years in direct people management and 3+ years managing other managers.

• Master's degree in Computer Science, or Bachelor's degree with equivalent experience

• Proven ability to lead, inspire, mentor, and grow large engineering teams and managers. Strong coaching skills.

• Significant hands-on technical background (software development, architecture, systems design). Ability to understand complex technical challenges and trade-offs deeply, even if not coding daily.

• Ability to set technical vision, translate business strategy into engineering execution, and make long-term architectural decisions.

• Proven track record of shipping complex, high-quality software products at scale. Expertise in Agile methodologies.

• Exceptional written and verbal communication skills. Ability to articulate complex technical concepts to both technical and non-technical audiences (including executives).

• Excellent interpersonal and stakeholder management skills. Ability to build strong cross-functional partnerships.

• Strong analytical and critical thinking skills. Ability to navigate ambiguity and make sound decisions under pressure.

• Experience establishing processes, metrics, and driving continuous improvement.

• Experience in ECommerce and Shipping industry

• Experience scaling engineering organizations during rapid growth

We are looking for exceptional engineering tech leaders and architects, who take pride in creating simple solutions to apparently-complex problems. Our Engineering tasks typically involve at least one of the following:

• Architect scalable data pipelines processing billions of items, integrating ML models.

• High availability site facing APIs getting billions of hits a day, with very low latency

• Craft API designs and drive integration between data layers and customer-facing applications.

• Design and run A/B tests in production to measure new functionality impact.

eBay is an amazing company to work for. Being on the team, you can expect to benefit from:

• A competitive salary - including stock grants and a yearly bonus

• A healthy work culture that promotes business impact and at the same time highly values your personal well-being

• Being part of a force for good in this world - eBay truly cares about its employees, its customers, and the world’s population, and takes every opportunity to make this clearly apparent

• Architect and drive strategic evolution of data pipelines, ML frameworks, and service infrastructure.

• Define and lead performance optimization strategies for critical systems.

• Collaborate on project scope and define long-term architectural vision.

• Develop and champion technical strategies aligned with business objectives.

• Lead cross-functional architectural initiatives, ensuring coherent solutions.

• Establish and champion organization-wide knowledge sharing and best practices.

• Passion and commitment for technical excellence

• B.Sc. or M.Sc. in Computer Science or an equivalent professional experience

• ​8+ years of software design, architecture, and development experience, tackling complex problems in backend services and / or data pipelines

• Solid foundation in Data Structures, Algorithms, Object-Oriented Programming, and Software Design

• Architectural expertise in production-grade systems using Java, Python/Scala, Java Script

• Strategic design and operational leadership of large-scale Big Data processing pipelines (Hadoop, Spark).

• Proven ability to resolve complex architectural challenges in production software systems.

• Executive-level communication and collaboration skills for influencing technical direction.