Top Tech Jobs & Startup Jobs

Design, build, and operate traffic management and routing systems for eBay’s large-scale commerce platforms. Develop high-performance services using Java, C++, or Go; deploy and troubleshoot Kubernetes workloads; improve security, latency, throughput, and reliability; and use observability tools for production diagnosis. Collaborate with SRE, platform, and application teams on distributed systems and networking solutions.

Conduct applied research on generative AI and foundation models, including LLMs, multimodal systems, agents, retrieval, post-training, and learning from feedback. Design experiments, develop and evaluate models, analyze large-scale marketplace data, and collaborate with engineering and product teams to productionize research. Contributions may include publications, patents, open-source work, and technical knowledge sharing.

Build and lead eBay’s Bangalore Platform Engineering team. Define the roadmap for Java developer platforms, frameworks, and CI/CD capabilities; provide technical leadership for scalable, secure platform services; improve developer productivity through automation and self-service tools; and partner with globally distributed engineering teams. The role requires ownership across development, testing, deployment, operations, reliability, and support.

Build and evolve eBay’s Java and Spring Boot developer platform, reusable frameworks, automation, and platform capabilities. Own features through design, testing, deployment, operations, and support. Develop CI/CD using Maven, Jenkins, Tekton, and Git, and operate cloud-native services with Docker and Kubernetes. Improve developer experience, reliability, observability, vulnerability management, security, and engineering productivity while collaborating with global engineering teams.

Leads and participates in risk-based regulatory audit engagements for eBay’s UK payment entity and other regions. Responsibilities include planning audits, evaluating laws, regulations, and controls, testing effectiveness, identifying root causes, reporting findings, tracking remediation, supporting annual risk assessments, and communicating results to management and risk forums. The role partners with Finance, Compliance, Product, IT, Risk, and Legal teams while monitoring evolving regulatory requirements.

eBay is hiring ML Scientists to design state-of-the-art ranking, recommendation, personalization, and pricing models, and ML Engineers to productionize models by building ETL/ELT workflows, inference pipelines, MLOps infrastructure, deployment automation, monitoring, and cost/ performance optimization. Both roles contribute to feature engineering, model serving, observability, and maintaining production ML platform components like Zipline.

Owns strategy, roadmap, priorities, and success measures for a developer platform area. Partners with engineers and architects to discover developer needs, evaluate technical tradeoffs, prioritize modernization and new capabilities, and drive delivery and adoption. Uses customer research, product data, and operational metrics to improve productivity, reliability, performance, cost, and satisfaction. Also identifies and scales responsible AI-enabled capabilities.

Lead the design, development, deployment, and continuous improvement of Generative AI and machine learning capabilities. Build systems involving LLMs, multimodal models, agents, retrieval, embeddings, model adaptation, and feedback-based learning. Make architectural decisions across the ML lifecycle, optimize quality, latency, cost, and reliability, and partner with research, engineering, product, and platform teams. Mentor engineers and provide hands-on technical leadership from experimentation through production.

The Senior Systems Engineer will design and develop data applications, lead software development teams, oversee data integration projects, manage BI systems, and ensure optimized performance while collaborating across teams.

Leads a team of applied researchers and machine learning engineers developing Generative AI products from research through production. Sets technical direction across LLMs, multimodal models, agents, retrieval, model adaptation, and feedback-based learning. Oversees training, evaluation, deployment, serving, and continuous improvement while balancing quality, latency, cost, reliability, and maintainability. Partners with product, engineering, research, and platform teams, and hires, mentors, and develops technical talent.