About the Role

As an Sr. Applied Research technical lead at eBay, you will be at the center of how multi-modal intelligence is applied across products. You will not just support AI development, you will lead a team of applied researchers and machine learning engineers to help define how AI driven solutions operate, scale, and deliver value. Your work will directly influence model quality, operational efficiency, and the ways AI enhances user experience across eBay.

Key Responsibilities

Team Development and Leadership:

Build and lead a high-functioning team of applied researchers and machine learning engineers. Create a collaborative environment focused on delivery, accountability, and skill growth.

Research and Development Ownership and AI Model Lifecycle Management

Own the creation, management, and evolution of multimodal solutions used across company's AI initiatives. Design structured processes for data acquisition, model training, and inference. Design,develop and improve large scale multimodal retrieval systems. Maintain high levels of model quality through both offline and online evaluations. Partner with internal teams and external providers to ensure that the right AI solutions and features are available for eBay use cases.

Cross-functional Collaboration:

Work with data scientists, engineers, and product managers to align AI solutions with eBay's goals. Translate research and product needs into development 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.

Process, Standards and Compliance

Establish and maintain clear standards for how data is collected, and models are trained and evaluations. Work with responsible AI teams to ensure model safety.

Metrics and Reporting:

Define key performance metrics for AI models. Maintain operational excellence standards for data pipelines and models in production

Skills and Expertise

Tools and Technical Fluency

Ph.D. in AI or equivalent research experience. Proficiency in Python and PyTorch for data processing, model training and inference. Expertise in Vision-Language Models and image/video retrieval. Deep understanding of key computer vision techniques for classification, image/video retrieval, 3D modeling, and Image/Video generation. Bonus: experience with frameworks for large-scale multi-GPU training (e.g. PyTorch Lightening, Nemo etc.) and for large scale inference (TensorRT, vLLM )

Team Leadership

Two years plus of experience as a tech lead or a manager of science/engineering teams. Comfortable coaching, and enabling team members to deliver high-quality work through clear direction, support, and collaboration.

Quality and Attention to Detail
Detail oriented in how you work with data, models, documentation, and process. Ability to catch inconsistencies early, ensuring standards are consistently met across workflows and deliverables.

Clarity in Communication and Problem Solving
Ability to clearly communicate with technical and non-technical teams, making complex issues easy to understand without oversimplifying. Ability to break down and clarify ambiguous problems, identify what's missing, and help teams move toward practical, well-defined solutions.

The base pay range for this position is expected in the range below:
$217,600 - $290,500

Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

If hired, employees will be in an "at-will position" and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

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