דרושים Applied Researcher T25 ב-איביי ב-India, Bengaluru

• Reliability & Performance: Design, implement, and maintain systems and processes to ensure the high availability, performance, and scalability of our production platform.

• Automation: Develop and implement automation for infrastructure provisioning, deployment, monitoring, and incident response, reducing manual toil and improving operational efficiency.

• Observability: Implement and enhance comprehensive monitoring, logging, and alerting solutions to provide deep insights into system health and performance.

• Incident Management: Lead incident response efforts, conduct root cause analyses, and implement preventative measures to minimize future occurrences.

• Capacity Planning: Collaborate with development teams to forecast resource needs and ensure the platform can handle anticipated growth and traffic spikes.

• System Design & Architecture: Provide input on system architecture and design, advocating for reliability, scalability, and operational best practices from the outset.

• Tooling & Infrastructure: Evaluate, select, and implement new tools and technologies to improve our platform's reliability, security, and operational capabilities.

• Collaboration & Mentorship: Work closely with development, QA, and security teams to embed reliability practices throughout the software development lifecycle. Mentor junior engineers on SRE principles and best practices.

• Documentation:

• Experience: 5+ years of experience in a DevOps, SRE, or similar role focused on platform reliability and operations.

• Cloud Platforms: Strong hands-on experience with at least one major cloud provider (e.g., AWS, Azure, GCP).

• Containerization & Orchestration: Expertise with Docker and Kubernetes for deploying and managing microservices.

• Infrastructure as Code: Proficiency with IaC tools such as Terraform, CloudFormation, or Ansible.

• Scripting & Programming: Strong scripting skills (e.g., Python, Bash) and experience with at least one compiled language (e.g., Go, Java, Node.js) for automation and tool development.

• Monitoring & Alerting: Experience with monitoring tools (e.g., Prometheus, Grafana, Datadog, New Relic) and logging systems (e.g., ELK Stack, Splunk).

• CI/CD: Solid understanding and experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).

• AI Code Generation: Familiarity with foundational AI concepts and practical experience applying AI-powered coding generation (e.g., OpenAI Codex, GitHub Copilot, Anthropic Claude, Cursor, Windsurf or understanding of transformer-based code generation) will be a significant asset.

• Networking: Fundamental understanding of networking concepts (TCP/IP, DNS, Load Balancing, Firewalls).

• Databases: Familiarity with database operations, performance tuning, and backup/recovery strategies (SQL and NoSQL).

• Problem-Solving: Exceptional analytical and troubleshooting skills, with a methodical approach to identifying and resolving complex system issues.

• Communication: Excellent verbal and written communication skills, capable of effectively communicating technical concepts to diverse audiences.

Machine Learning Engineer (T25), Product Knowledge

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

• Building a pipeline that processes up to billions of items, frequently employing ML models on these datasets

• Creating services that provide Search or other Information Retrieval capabilities at low latency on datasets of hundreds of millions of items

• Crafting sound API design and driving integration between our Data layers and Customer-facing applications and components

• Designing and running A/B tests in Production experiences in order to vet and measure the impact of any new or improved functionality

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

• Design, deliver, and maintain significant features in data pipelines, ML processing, and / or service infrastructure

• Optimize software performance to achieve the required throughput and / or latency

• Work with your manager, peers, and Product Managers to scope projects and features

• Come up with a sound technical strategy, taking into consideration the project goals, timelines, and expected impact

• Take point on some cross-team efforts, taking ownership of a business problem and ensuring the different teams are in sync and working towards a coherent technical solution

• Take active part in knowledge sharing across the organization - both teaching and learning from others

• Passion and commitment for technical excellence

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

• ​4+ years of software design and development experience, tackling non-trivial problems in backend services and / or data pipelines

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

• Experience in production-grade coding in Java, and Python/Scala

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

• ​Experience in designing and operating Big Data processing pipelines, such as: Hadoop and Spark

• ​Excellent verbal and written communication and collaboration skills

• Quality Strategy & Planning: Collaborate with product managers, developers, and other stakeholders to define comprehensive quality strategies and test plans for new features and existing functionalities across our ReactJS frontend and Node.js/Java backend services.

• Test Automation Development: Design, develop, and maintain robust and scalable automated test suites using frameworks like Jest, React Testing Library, and Cypress for frontend applications, and integrate with backend testing frameworks for Java/Node.js services.

• Performance & Scalability Testing: Conduct performance, load, and scalability testing to identify bottlenecks and ensure our applications meet high-performance standards, working closely with backend engineers on distributed systems.

• Functional & Integration Testing: Lead the execution of functional, integration, and end-to-end tests to validate software behavior, data integrity, and API interactions.

• Defect Management: Identify, log, and prioritize defects, working closely with development teams to ensure timely resolution and retesting.

• CI/CD Integration: Integrate automated tests into the CI/CD pipelines to enable continuous testing and rapid feedback loops.

• Mentorship & Best Practices: Promote and drive quality best practices within the team, providing guidance and mentorship to junior and mid-level engineers on testing methodologies, tools, and automation.

• Troubleshooting & Root Cause Analysis: Assist in diagnosing and debugging complex technical issues, collaborating with development teams to perform root cause analysis.

• Tooling & Innovation: Research and evaluate new testing tools, technologies, and methodologies to enhance our quality assurance processes and efficiency.

• Cross-functional Collaboration:

• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.

• Experience: 5+ years of progressive experience in software quality assurance, with a strong focus on test automation for web applications.

• Frontend Testing Expertise: Strong experience with testing frameworks like Jest, React Testing Library, and Cypress for ReactJS applications.

• Backend Testing: Experience with testing RESTful APIs and/or GraphQL services. Familiarity with testing Java-based backend services (e.g., using JUnit, Mockito) and Node.js backend services.

• Test Automation Architecture: Proven ability to design and implement robust, scalable, and maintainable automated test frameworks.

• Web Technologies: Good understanding of modern web technologies, including HTML5, CSS3, JavaScript (ES6+), and TypeScript.

• AI Code Generation: Familiarity with foundational AI concepts and practical experience applying AI-powered coding generation (e.g., OpenAI Codex, GitHub Copilot, Anthropic Claude, Cursor, Windsurf or understanding of transformer-based code generation) will be a significant asset.

• Version Control: Proficiency with Git and collaborative development workflows.

• Problem Solving: Excellent analytical and problem-solving skills, with a keen eye for detail.

• Communication: Strong verbal and written communication skills, with the ability to effectively communicate technical information and collaborate across teams.

• Agile Methodologies: Experience working in an Agile/Scrum development environment.

• Experience with performance testing tools (e.g., JMeter, LoadRunner).

• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).

• Experience with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI).

• Knowledge of database testing (relational and NoSQL).

• Experience with security testing principles.

• Understanding of micro-frontend architectures.

• Familiarity with AI systems and tools, and experience with AI coding tools (e.g., GitHub Copilot) for test script generation.

We are seeking a highly motivated and experienced Senior Platform Reliability Engineer (PRE) to join our growing team. In this critical role, you will be responsible for ensuring the reliability, scalability, and performance of our core platform and services. You will apply Site Reliability Engineering (SRE) principles to automate operations, improve system resilience, and drive a culture of continuous improvement across our engineering organization.

• Reliability & Performance: Design, implement, and maintain systems and processes to ensure the high availability, performance, and scalability of our production platform.

• Automation: Develop and implement automation for infrastructure provisioning, deployment, monitoring, and incident response, reducing manual toil and improving operational efficiency.

• Observability: Implement and enhance comprehensive monitoring, logging, and alerting solutions to provide deep insights into system health and performance.

• Incident Management: Lead incident response efforts, conduct root cause analyses, and implement preventative measures to minimize future occurrences.

• Capacity Planning: Collaborate with development teams to forecast resource needs and ensure the platform can handle anticipated growth and traffic spikes.

• System Design & Architecture: Provide input on system architecture and design, advocating for reliability, scalability, and operational best practices from the outset.

• Tooling & Infrastructure: Evaluate, select, and implement new tools and technologies to improve our platform's reliability, security, and operational capabilities.

• Collaboration & Mentorship: Work closely with development, QA, and security teams to embed reliability practices throughout the software development lifecycle. Mentor junior engineers on SRE principles and best practices.

• Documentation:

• Experience: 5+ years of experience in a DevOps, SRE, or similar role focused on platform reliability and operations.

• Cloud Platforms: Strong hands-on experience with at least one major cloud provider (e.g., AWS, Azure, GCP).

• Containerization & Orchestration: Expertise with Docker and Kubernetes for deploying and managing microservices.

• Infrastructure as Code: Proficiency with IaC tools such as Terraform, CloudFormation, or Ansible.

• Scripting & Programming: Strong scripting skills (e.g., Python, Bash) and experience with at least one compiled language (e.g., Go, Java, Node.js) for automation and tool development.

• Monitoring & Alerting: Experience with monitoring tools (e.g., Prometheus, Grafana, Datadog, New Relic) and logging systems (e.g., ELK Stack, Splunk).

• CI/CD: Solid understanding and experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).

• AI Code Generation: Familiarity with foundational AI concepts and practical experience applying AI-powered coding generation (e.g., OpenAI Codex, GitHub Copilot, Anthropic Claude, Cursor, Windsurf or understanding of transformer-based code generation) will be a significant asset.

• Networking: Fundamental understanding of networking concepts (TCP/IP, DNS, Load Balancing, Firewalls).

• Databases: Familiarity with database operations, performance tuning, and backup/recovery strategies (SQL and NoSQL).

• Problem-Solving: Exceptional analytical and troubleshooting skills, with a methodical approach to identifying and resolving complex system issues.

• Communication: Excellent verbal and written communication skills, capable of effectively communicating technical concepts to diverse audiences.

Education: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

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

​Job Responsibilities

• Collaborate with Management and Product Management on shaping the department’s vision and roadmap

• Help define and refine project scopes, goals, and metrics

• ​Seek scientifically valid solutions that deliver real value to eBay customers

• Carefully measure your output and impact in order to learn and improve over time

• Collaborate with Operations team to ensure the quality of any human-labeled data required

• ​Build Machine Learning models and data pipelines to deliver insightful yet practical solutions

• Mentor more junior peers, as well as review their work and provide frequent feedback and advice

• Promote Scientific rigor and standards, as well as code quality and craftsmanship within the team - especially among your less experienced peers

• ​Present key technical and novel research work in public forums and conferences

• Help interview and hire additional, exceptional teammates!

Minimum Qualifications

• ​BE/B.Tech with 10+ years of relevant Industry experience

• M.Sc. or Ph.D. in Computer Science, Statistics, Mathematics, or equivalent field with 7+ years of industrial experience in Applied Machine Learning

• ​Industrial experience with multiple of the following: classification, regression, NLP, clustering, Deep Learning / Neural Networks, Reinforcement Learning, or related

• Significant Experience in Production-grade coding in a high-level language such as Python or Java

• ​Experience in Big Data processing frameworks, e.g. Hadoop, SQL, Spark

• ​Excellent verbal and written communication and collaboration skills

• Thought leadership and mentoring skills

Additional Qualifications

• ​5 or more related publications/patents in quality conferences or journals

• Open source tool building/commits to popular threads.

• Experience on Language models and KG building

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

Key Responsibilities

• Drive Strategy & Vision : Partner with senior leadership, product management, and other stakeholders to define and execute the machine learning roadmap aligned with business goals.

• Team Leadership : Lead, mentor, and grow a team of ML scientists and engineers. Create an environment that encourages innovation, high performance, and career development.

• Technical Oversight : Guide and review the development of machine learning models and data pipelines, ensuring scalability, scientific validity, and production readiness.

• Cross-Functional Collaboration : Collaborate with Product and Analytics teams to scope projects, prioritize initiatives, and ensure seamless data and model integration.

• Operational Excellence : Define project goals, success metrics, and delivery timelines. Ensure effective resource allocation and continuous improvement in team processes.

• Foster Scientific Rigor : Uphold high standards of experimentation, measurement, and peer review. Promote the use of reproducible research and robust evaluation practices.

• Data Strategy : Partner with the operations and data teams to ensure access to high-quality labeled data, and proactively shape data acquisition strategies where needed.

• Talent Development : Provide coaching and technical guidance to team members. Conduct performance reviews, identify skill gaps, and invest in team capability building.

• Hiring

Minimum Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field with 6+ years of relevant industry experience, including 3+ years in people management.

• Proven experience leading machine learning teams in an applied industrial setting.

• Deep understanding of modern ML approaches including classification, regression, NLP, clustering, deep learning, and/or reinforcement learning.

• Strong programming background in Python, Java, or similar, with exposure to production-grade ML systems.

• Proficiency with big data processing frameworks such as Hadoop, Spark, and SQL.

• Excellent communication, storytelling, and stakeholder management skills.

• Demonstrated ability to translate business needs into scientific problems and to prioritize for impact.
  

Additional Qualifications

• Master’s or Ph.D. in a relevant field (Computer Science, ML, Stats, etc.)

• Track record of impactful publications and/or patents in machine learning or related areas.

• Contributions to open-source ML tools or frameworks.

• Experience with modern large language models, graph-based ML, or knowledge graph construction.

• Strong presence in scientific communities through talks, panels, or organizing roles.