AI Applied Scientist

🕒 May 21

🇺🇸 United States – Remote

💵 $225k - $280k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧬 Research Scientist

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Wizard

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🛍️ eCommerce

🛒 Retail

💰 $50M Series A on 2021-10

Artificial Intelligence • eCommerce • Retail

Wizard AI is a company that provides a tailored shopping experience powered by artificial intelligence. It offers a unique text-based service that curates product recommendations across the internet, utilizing AI models that understand user preferences to predict needs and make personalized suggestions. Wizard AI simplifies shopping by finding, ordering, and tracking products, as well as managing returns through SMS communication. This service is designed to save time and improve the convenience of online shopping by efficiently juggling product data, customer reviews, and other digital content to make informed recommendations for customers.

📋 Description

• Define and evolve accuracy metrics across the full shopping experience (retrieval, ranking, recommendations, outcomes) • Design and run experiments to measure improvements and regressions • Build and maintain evaluation datasets, benchmarks, and scoring frameworks • Improve the LLM judges that power our evaluation pipeline: prompting, calibration, and fine-tuning where it matters • Translate ambiguous product questions into clear, measurable hypotheses and analysis • Partner with ML Engineers to validate model changes and guide iteration • Identify failure modes and edge cases, and drive improvements through data • Make agent performance visible, trusted, and actionable across product and engineering

🎯 Requirements

• 5+ years in Applied ML, AI Research, or Applied Science (PhD or equivalent depth strongly preferred) • Hands-on experience evaluating modern AI/ML systems: LLMs, agents, ranking, or recommendations • Direct experience with LLM-based systems: judge models, RAG, prompt engineering, fine-tuning, RLHF, or similar • Strong experimentation foundations: A/B testing, causal inference, statistical rigor • Proven ability to operate in ambiguity: defining problems, not just solving pre-defined ones • Clear, structured communication that influences across ML, engineering, and product.

🏖️ Benefits

• Equity in the form of stock options • Medical, dental, and vision coverage • 401(k) plan • Flexible PTO and company holidays • Fully remote work within the United States • Periodic company offsites and team gatherings