Applied Research Scientist

Responsibilities

• Train, test, and ship models that power Peec AI's recommendations - helping customers boost their visibility in AI search
• Develop algorithms that extract insights from consumer search behavior, predict which questions people are asking and which topics are coming up.
• Partner with engineering to bring your models into production
• Leverage existing data pipelines and infrastructure to run experiments and validate your research at scale
• Support the team's work on autonomous agentic systems that collect, verify, and structure information from across the web
• Work with web-scale data - building crawlers, working with clickstream data, analyzing large-scale internet signals like URLs, keywords, and user behavior

Requirements

• A deep interest in online consumer behavior
• Strong statistical and quantitative foundations with experience in statistical modeling, hypothesis testing, causal inference, or Bayesian methods
• Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features
• Track record of taking projects from research to production, with strong problem-solving skills and comfort working with ambiguous, evolving problems
• Familiarity with NLP techniques like ranking models, text classification, embeddings, or information retrieval
• Excellent communication skills with the ability to explain complex technical concepts to stakeholders
• Our Data Science Stack
• Languages : Python, SQL
• Libraries : Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX
• Backend : GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery
• AI Models : OpenAI, Claude, Perplexity, Gemini, Llama, etc.
• Bonus Points
• Contributions to open-source projects
• Deployed side/hobby projects that we can check out
• Presented research papers at top ML or AI conferences
• Having started a company before or worked at a high-growth startup
• Fluency in Typescript

Benefits

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Company Intel

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