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Company Overview
A leading global e-commerce company is seeking a Machine Learning Scientist II to join their Catalog Science team. This team drives innovation in product understanding, relationships modeling, and AI-powered catalog intelligence at scale. Their work enhances customer browsing experiences, streamlines supplier product onboarding, and ensures accurate, high-quality catalog data, delivering measurable business impact across the organization.
Summary
The Machine Learning Scientist II will develop and refine advanced models and systems powering catalog intelligence. This role involves research, experimentation, and deployment of state-of-the-art deep learning, vision-language models, and generative AI workflows. You will collaborate with cross-functional teams to deliver scalable AI solutions that directly impact business operations and customer experiences.
Responsibilities
Research and experiment with multi-modal understanding techniques and algorithms
Design and implement evaluation strategies for real-world catalog applications
Leverage and fine-tune LLMs (e.g., OpenAI GPT, Google Gemini, Anthropic Claude, Open Source) for classifiers, product taggers, and quality control
Develop and enhance visual search systems using computer vision and vision-language models
Implement AI automation for product data structuring, attribute extraction, and metadata validation
Collaborate with AI research leaders and cross-functional teams to explore cutting-edge techniques
Develop agentic AI workflows for automated schema definition, dataset generation, and catalog validation
Optimize AI models for efficiency, cost, and scalability using fine-tuning, knowledge distillation, and hybrid approaches
Ensure AI solutions integrate seamlessly with catalog systems and engineering pipelines
Qualifications
PhD in Computer Science, Machine Learning, Electrical Engineering, Physics, or related field, OR MS with 2+ years of relevant experience
Deep expertise in machine learning, deep learning, reinforcement learning, and multi-modal understanding
Hands-on experience with LLMs, VLMs, generative AI, fine-tuning, RAG, and models such as GPT, Gemini, Claude, or open-source alternatives
Professional coding skills in Python or Go, proficiency in SQL, and experience with ML frameworks (TensorFlow, PyTorch)
Familiarity with CI/CD, containerization, version control (git), and scalable data processing pipelines
Strong analytical, problem-solving, and communication skills; able to explain complex AI concepts to non-technical stakeholders
Ability to learn new tools quickly and manage multiple priorities in a fast-paced environment
Proven track record of delivering machine learning projects from conception to production
Background in e-commerce catalog AI systems, retail data structuring, or large-scale product classification
Research publications in deep learning, computer vision, or generative AI
Experience with autonomous AI agents, reinforcement learning, or online learning systems
Disclaimer
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