Machine Learning Scientist II – Catalog Science

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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

Nice to Have

• Experience with MLOps, cloud infrastructure (Google Cloud Platform), Airflow/Composer, Kubeflow, MLFlow, Kubernetes, VertexAI, Spark, DataDog, Arize
• 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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