Role Overview :

We are hiring a Lead AI Engineer to provide hands-on technical leadership for AI systems powering ecommerce search, retrieval, ranking, personalization, and visual discovery.

This is a senior individual-contributor role centered on research, rapid experimentation, production engineering, and measurable business impact across text, image, and multimodal experiences.

You will set technical direction and lead end-to-end AI solutions across matching, multimodal retrieval, ranking, computer vision, vision-language modeling, and GenAI-powered experiences from problem framing and research through deployment, evaluation, and iteration at scale.

You will also mentor engineers and scientists, establish reusable technical patterns, and influence cross-functional product and platform roadmaps.

Core Responsibilities:

- Set technical direction and lead research, experimentation, and production delivery for ML models spanning product matching, semantic/visual retrieval, search relevance, and image understanding.

- Architect and optimize multi-stage retrieval and ranking pipelines across text, image, and fused multimodal representations.

- Develop, fine-tune, and evaluate computer vision, vision-language, and multimodal models.

- Create rigorous offline evaluation, benchmarking, and online experimentation frameworks.

- Apply reinforcement learning, learning-to-rank, or bandit methods for personalization.

- Build and deploy GenAI and agentic AI systems.

- Lead model and data strategy for multimodal systems, ensuring robustness, bias mitigation, and safety.

- Productionize ML systems using Databricks and AKS, designing for latency, throughput, and observability.

- Establish reusable architectures and MLOps/LLMOps practices.

Required Qualifications:

- 6+ years of experience in machine learning, applied science, or ML engineering, including leading complex initiatives.

- 2+ years of hands-on experience developing and fine-tuning computer vision models.

- Deep expertise in at least two of: Search/Retrieval/Ranking, Computer Vision, or Vision-Language/Multimodal models.

- Strong proficiency in Python and PyTorch or equivalent.

- Hands-on experience with Databricks, distributed pipelines, and Kubernetes/AKS.

- Demonstrated technical leadership and ability to communicate complex trade-offs.