Senior AI Platform Architect
| Company | eBay |
|---|---|
| Location | Austin, TX, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- PhD or MS in Computer Science, Electrical Engineering or related field.
- 8+ years of experience in software engineering with a focus on large-scale, high-performance distributed systems.
- Proven experience in designing and architecting sophisticated systems at scale, with expertise in distributed systems, microservices, and event-driven architectures.
- Strong programming skills in Python, Java or C, with experience in frameworks like TensorFlow, PyTorch.
- In-depth understanding and experience with high-performance databases (SQL, NoSQL), vector databases, Graph databases, and experience working with or understanding generative models, RAG.
- Strong skills in scalability and performance tuning for high-volume, critical applications, ensuring robust and resilient AI frameworks.
- Experience leading multi-functional projects, providing strategic technical leadership, and influencing the direction of engineering practices across an organization.
- Proven track record of leading and participating in effort estimation for complex projects, ensuring that project timelines and resources align with business objectives.
- Exceptional problem-solving skills with a focus on innovation, scalability, and performance optimization in AI solutions.
- Strong Communication: Excellent communication and leadership skills, capable of engaging both technical and non-technical partners at all organizational levels.
- Agile Methodologies: experience with Agile/Scrum methodologies.
- Experience with or understanding of some of the following technologies: Docker, Kubernetes, Spark, Hadoop, Kafka, MLflow, Airflow, Kubeflow, Nvidia Triton, Nvidia TensorRT, vLLM, Ray.io.
Responsibilities
- Design and implement robust, scalable and secure systems for the eBay AI Platform, supporting all stages of development of an AI application, including data preparation, model training, model serving, experimentation, observability.
- Evaluate emerging technologies and frameworks to enhance platform capabilities. Lead the adoption of tools and methods to optimize performance and cost efficiency.
- Mentor and coach engineers at all levels, supporting their professional development and helping grow the technical capability of the team.
- Collaborate with senior technical leaders across various domains to ensure architecture alignment, module reuse, performance optimization, data consistency, and high availability of AI solutions.
- Foster a culture of engineering excellence by driving efficiency, velocity, quality, and innovation within the team, and lead initiatives to modernize the technology stack when advantageous.
- Actively participate in the software development process by investigating issues, writing high-quality code, performing rigorous code reviews, and prototyping innovative solutions.
Preferred Qualifications
- Experience with or understanding of some of the following technologies: Docker, Kubernetes, Spark, Hadoop, Kafka, MLflow, Airflow, Kubeflow, Nvidia Triton, Nvidia TensorRT, vLLM, Ray.io.