Lead Generative AI Engineer

We are seeking an experienced and visionary Technical Lead, Machine Learning Engineering to drive the technical direction and execution of our next generation personalization systems, including our Multimodal Recommendation Engine and emerging generative AI initiatives. You will work with massive scale datasets across our retail ecosystem to build sophisticated personalization experiences

What You'll Do As a Technical Lead

• Technical Leadership & Architecture

• Lead the design, architecture, and implementation of highly scalable and robust machine learning systems for personalization, ensuring technical excellence and alignment with strategic goals.

• Drive technical strategy and roadmap decisions for the personalization platform, identifying opportunities for innovation and improvement.

• Define and enforce best practices for MLOps, code quality, testing, and maintainability across the team.

Team Leadership & Mentorship

• Mentor and guide a team of talented ML engineers fostering their technical growth.

• Conduct thorough code reviews, provide constructive feedback, and promote a culture of continuous learning and collaboration.

• Lead by example in coding, system design, and tackling complex technical challenges.

• System Development & Optimization

• Architect and implement advanced deep learning models for multimodal recommendations and generative AI, with a strong emphasis on leveraging techniques like Retrieval Augmented Generation (RAG) and frameworks such as LangChain to build robust and context-aware applications.

• Oversee the design and maintenance of highly scalable ML infrastructure using GCP services (Vertex AI, BigTable, BigQuery, Cloud Composer) capable of handling millions of daily predictions, including the strategic integration and management of vector databases for efficient similarity search and retrieval.

• Lead the end-to-end development and optimization of ML pipelines for model training, deployment, and monitoring at scale.

Collaboration & Strategy

• Collaborate closely with Product Managers, Data Scientists, and other engineering teams to translate complex business requirements into robust, scalable technical solutions.

• Lead experimentation strategies with measurable KPIs, including adoption, conversion, and retention.

• 7+ years of experience in machine learning engineering, with a strong focus on recommendation systems, personalization, or large-scale AI.

• 2+ years of experience in a technical leadership role, demonstrating proven ability to lead projects, mentor engineers, and drive technical initiatives.

• Proven track record of architecting, building, and deploying production-grade ML systems at scale.

• Deep expertise in deep learning frameworks (PyTorch or TensorFlow) and MLOps best practices, with significant hands-on experience in Generative AI models (e.g., LLMs), RAG architectures, and practical application of frameworks like LangChain and vector databases.

• Extensive experience with GCP services (Vertex AI, BigTable, BigQuery, Cloud Composer) and cloud-native development.

• Proficiency in Python and SQL.

• Exceptional problem-solving, communication, and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences. Preferred Qualifications

• Experience with multimodal deep learning architectures.

• Knowledge of modern recommendation system architectures (transformers, neural collaborative filtering).

• Expertise in building real-time inference systems.

• Experience with distributed computing frameworks (Spark) and big data processing.

• Familiarity with containerization (Docker) and orchestration (Kubernetes).

• Experience with CI/CD pipelines

Required Qualifications

• Master's or PhD in Computer Science, Machine Learning, or a related quantitative field.