Ai Dataops Lead jobs at Ebay in Netherlands, Amsterdam

What you will accomplish:

• Native iOS app development and converting ideas, designs and requirements to concrete stable production builds. Understand and implement iOS specific design patterns.

• Develop and iterate within a rather lean, yet very fast-paced Engineering team.

• Attracting, recruiting, hiring, and retaining a team of native iOS engineers.

• Growing your team through coaching, mentoring, and consistent one-on-one conversations.

• Leading agile development processes, including planning, implementation, testing, demos, and retrospectives for your team.

• Getting into the details, investigating issues, writing code, performing code reviews, and prototyping new solutions.

• Providing expert feedback for code quality, performance, scalability, system architecture, and engineering methodologies.

• Collaborating effectively with product development and engineering teams across multiple domains and multiple geographies.

• Focusing on continuous improvement in our practices, driven from the ground up. We will expect you to advocate for improvements in code and culture, and to support your team in the same.

• Manage a small team of iOS engineers.

What you will bring:

• Your passion for engineering, quality, agility and more.

• 10+ years proven experience in designing, building, refactoring and releasing rich client software using industry standard patterns.

• Experience with iOS XCode, Swift, Swift UI, debuggers (e.g. Charles), revision control systems (e.g. Git) and bug tracking (e.g. Jira). TCA is a plus

• Experience in integration with backend APIs (REST/GraphQL)

• Proven ability to lead the development of multiple features of an application and coordinating cross-team consensus and delivery of a product release.

• Experience with TDD, pairing, code reviews, and other techniques to maintain high-quality code and resiliency.

• Advocacy of automated testing, continuous delivery, and software quality across the software development life cycle.

• Proven track record in successfully delivering large scale enterprise-wide solutions, from design to development to testing to production.

• Be open to having a few iOS engineers report to you, having people management experience is a plus.

• Preferred experience with Swift’s Combine framework: Functional programming, reactive software architecture, decoupled APIs, TCA architecture.

• Excellent understanding of S.O.L.I.D principles and the ability to apply them on their day to day software development.

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

• Experience in Agile/Scrum/Kanban methodologies and working in an agile engineering team.

You will not just support AI development. You will help define how it operates, scales, and delivers value. Your work will directly influence model quality, operational efficiency, and the ways AI enhances user experience across eBay.

• Team Development and Leadership: Build and lead a high-functioning team of analysts and data engineers. Create a collaborative environment focused on delivery, accountability, and skill growth.
• Data Ownership and Lifecycle Management: Own the creation, management, and evolution of datasets used across company’s AI initiatives. Design structured processes for data acquisition, annotation, enrichment, and storage. Partner with internal teams and external providers to ensure the right data is collected, accurately labeled, and available at the right time.
• Labeling at Scale: Design and operate scalable labeling pipelines that serve a wide range of AI use cases. Define task structures, prepare data for annotation, and ensure consistent labeling quality through strong guidelines and validation processes. Collaborate closely with third-party providers to align on expectations, manage throughput, and monitor data quality across the full lifecycle of the engagement. Treat labeling not as an isolated task, but as a strategic capability that feeds directly into model success.
• Cross-functional Collaboration: Work with data scientists, engineers, and product managers to align data operations with AI goals. Translate research and product needs into data plans and workflows.
• Operational Strategy: Create work plans that reflect team priorities and long-term objectives. Adapt quickly to changing needs while keeping the team focused on outcomes that matter.
• Budget Oversight: Manage budgets tied to external partnerships and workforce resources. Make cost-effective decisions that support operational goals without compromising quality.
• Process, Standards and Compliance: Establish and maintain clear standards for how data is collected, structured, stored, and used across initiatives. Ensure all practices meet internal policy, legal, and privacy requirements, especially around the handling of sensitive or regulated information. Maintain high levels of data quality by enforcing consistency, managing taxonomies and ontologies, and ensuring datasets remain well-organized, traceable, and usable at scale.
• Analytics and Insight Development: Lead ongoing analysis efforts to extract insight from data that informs product direction, model performance, and operational decision making. Build a foundation for analytics as a core capability within the team, not just a reactive function.
• Metrics and Reporting:

• Team Leadership: Three to five years of experience managing teams. Comfortable hiring, coaching, and enabling team members to deliver high-quality work through clear direction, support, and collaboration.
• Tools and Technical Fluency: Proficient in Python for data processing, automation, and scripting tasks. Skilled in efficient data querying and retrieval using SQL. Comfortable working with large-scale systems such as Hadoop, and experienced in using Tableau and similar tools to build structured reporting and analytics workflows. Able to design data pipelines that are reliable, maintainable, and scalable.
• Dashboard and Reporting Design: Able to build reporting systems that serve engineering, research, and business audiences. You know how to turn raw data into dashboards that are reliable, insightful, and action-ready.
• Quality and Attention to Detail: You are thorough in how you work with data, documentation, and process. You catch inconsistencies early, verify accuracy before moving forward, and ensure standards are consistently met across workflows and deliverables.
• Clarity in Communication and Problem Solving:
  

As a Lead iOS Developer on the Core AI team, you’ll help build AI-first user experiences that power key features in the eBay mobile apps. Our team delivers generally applicable AI solutions and owns the full stack, from research to production. You’ll work in a tight-knit, cross-functional group that includes engineers, product managers, researchers, ML Ops and analytics.

You'll collaborate across domain teams and work side-by-side with other native developers in an agile environment. Partnering with product, design, and analytics, you'll craft user-centric features that leverage the latest AI technologies. This is a great opportunity to work on challenging problems with real impact and help define how AI shows up in mobile experiences at scale.

What you will accomplish:

• Lead the design and development of sophisticated iOS applications for Core AI, focusing on delivering exceptional user experiences and robust functionality.

• Collaborate with cross-functional teams, including product managers, designers, and other developers, to define app features, architecture, and technology stack.

• Collaborate with other eBay iOS and mobile engineering teams on common components, and cross domain functionality.

• Oversee and write high-quality, maintainable, and efficient code, adhering to best practices and industry standards.

• Oversee and write the testing and debugging of applications to ensure optimal performance, scalability, and reliability.

• Keep abreast of the latest iOS development trends and technologies, actively contributing to the continuous improvement of skills and knowledge within the team.

• Conduct thorough code reviews, providing mentorship and guidance to junior developers.

• Lead the troubleshooting and resolution of complex issues reported by users or identified during testing.

• Develop and maintain comprehensive app documentation, including architecture diagrams and API specifications.

What you will bring:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.

• 7+ years of experience in iOS development, with a strong portfolio of sophisticated, widely-used apps.

• Expertise in Swift and Objective-C, and extensive experience with iOS frameworks such as Swift UI, UIKit, Core Data, and Core Animation.

• In-depth knowledge of RESTful APIs and JSON to connect iOS applications to back-end services.

• Solid understanding of Apple's design principles and interface guidelines.

• Experience with cloud message APIs, push notifications, and mobile analytics.

• Proficiency with version control tools such as Git, and familiarity with CI/CD practices.

• Exceptional problem-solving skills, attention to detail, and ability to think strategically.

• Excellent leadership, communication, and teamwork skills.

Preferred Qualifications:

• Previous experience in e-commerce application development.

• Strong familiarity with Agile development methodologies.

• Working with GraphQL based services

• Experience in leading development teams and mentoring junior developers.

• Architect and design of high-performance storage system for GPU cluster, supporting large checkpoints and low-latency context preemption and reloads.

• Develop monitoring and observability tools for GPU clusters

• Maintain high availability, fault tolerance, and disaster recovery strategies for AI infrastructure

• Work closely with AI/ML engineers, data scientists, and DevOps teams to streamline AI workflows.

What you will bring:

• Masters or PhD in EE or CS

• Over 5 years of experience building HPC systems

• C/C++ Programming – for performance-critical components and integration tasks. Lustre (Paralell filesystems is in C)

• Linux Kernel and OS internals – to optimize system behavior and support kernel-level customization for filesystems and networking

• Filesystems knowledge – with a strong preference for experience in Lustre or similar distributed filesystems

• Kubernetes – for container orchestration and management at scale

• Hardware and Networking familiarity – to work effectively with low-level infrastructure and tuning

Good to have:

• Strong understanding of RDMA, RoCE V2 protocols

• Hands-on experience with GPUs

• Understanding of AI Workflows, training, inferencing

• Understanding of AI/ML Python frameworks (TensorFlow, PyTorch)

We are seeking a highly skilled and experienced Software Engineer to design, develop, and optimize systems and applications in our Machine Learning (ML) platform. We want the highest levels of technical talent and programming skills, as well as a keen desire to deeply understand our products and services to push our technology forward. You’ll work alongside the most creative engineering talent in the industry around the world.
As an AI Platform Software Engineer, you will work closely with engineering teams, data scientists, and business partners to develop systems that support high-performance model training, deployment, and monitoring. What you will accomplish:

• Design and implement robust, scalable, and secure systems to support a wide range of machine learning use cases, including large-scale training, real-time inference, and agentic AI applications.

• Evaluate and adopt emerging technologies and frameworks to enhance platform capabilities, optimize GPU usage, and improve performance and cost efficiency for high-throughput model serving.

• Collaborate with cross-functional teams, including data engineers, software engineers, data scientists, product managers, and researchers, to align platform development with business goals and integrate new LLM and agentic features.

• Define and implement end-to-end automated ML workflows covering data preprocessing, model training, hyperparameter tuning, deployment, and monitoring.

• Architect and build APIs, services, and orchestration layers tailored for LLMs and agentic AI, using frameworks like LangChain, Langfuse, Spring AI, and LlamaIndex to accelerate feature development.

• Ensure adherence to enterprise-level governance, security, and compliance standards while maintaining scalability, reliability, and maintainability across both production and experimental environments.
  

What you will bring:

• BS, MS, or PhD in Computer Science, Engineering, or a related field, with 4+ years of software development and architecture experience, including at least 2 years focused on machine learning platforms.

• Proven expertise in designing and building ML platforms, including training pipelines, inference services, and large-scale, secure APIs to support LLM-based and agentic applications.

• Strong programming skills in Python, Java, or Scala, with hands-on experience using ML frameworks such as TensorFlow or PyTorch.

• Familiarity with containerization and orchestration tools like Docker and Kubernetes, as well as big data technologies including Spark, Hadoop, and Kafka.

• Experience with MLOps practices, including CI/CD pipelines and tools such as MLflow or Kubeflow; familiarity with is a plus.

• Demonstrated success implementing AI/LLM solutions at scale and collaborating with product and research teams to deliver experimental and production-ready AI-driven features using frameworks like LangChain, LlamaIndex, and Spring AI.

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Infrastructure Design & Optimization

• Architect, develop and deploy scalable AI/ML infrastructure using Kubernetes, Docker, and containerized solutions.

• Configure & Optimize GPU, TPU, and high-performance compute resources for efficient training and inference.

• Implement cloud-based AI solutions and integrate with on-prem environments.

• Design high-speed networking and storage solutions to support AI workloads. Strong understanding of RDMA, RoCE V2 protocols.

• Working and Managing experience with Nvidia SuperPOD.

• Deep understanding and hands on experience on Parallel File Systems (Lustre)

AI/ML Pipeline Performance & Automation

• Optimize distributed training workflows.

• Implement automated deployment pipelines.

• Ensure cost-efficient resource utilization by tuning cloud auto-scaling, spot instances, and job scheduling.

Monitoring, Security & Compliance

• Develop observability and monitoring tools using Prometheus, Grafana.

• Ensure AI workloads comply with security best practices (RBAC, IAM, encryption).

• Maintain high availability, fault tolerance, and disaster recovery strategies for AI infrastructure.

• AI/ML engineers, data scientists, and DevOps teams to streamline AI workflows.

• Stay ahead of emerging AI infrastructure trends

• 3-7 years of experience in AI/ML infrastructure, DevOps, or HPC environments .

• Strong expertise in Linux, Kubernetes, and container orchestration .

• Hands-on experience with GPUs, TPUs, or AI accelerators .

• Knowledge of storage architectures, distributed file systems (Lustre), and data lakes .

• Experience with monitoring, logging, and automation tools (Prometheus, ELK, Grafana, Python, Bash) .

• Strong understanding of AI/ML frameworks (TensorFlow, PyTorch)

• Excellent problem-solving skills and ability to work in a fast-paced AI/ML environment .

• Expert level experience on C programming knowledge.

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