WHAT YOU’LL DO
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Train, test, and ship models that power Peec AI's recommendations — helping customers boost their visibility in AI search
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Develop algorithms that extract insights from consumer search behavior, predict which questions people are asking and which topics are coming up.
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Partner with engineering to bring your models into production
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Leverage existing data pipelines and infrastructure to run experiments and validate your research at scale
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Support the team's work on autonomous agentic systems that collect, verify, and structure information from across the web
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Work with web-scale data - building crawlers, working with clickstream data, analyzing large-scale internet signals like URLs, keywords, and user behavior
WHAT WE’RE LOOKING FOR
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A deep interest in online consumer behavior
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Strong statistical and quantitative foundations with experience in statistical modeling, hypothesis testing, causal inference, or Bayesian methods
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Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features
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Track record of taking projects from research to production, with strong problem-solving skills and comfort working with ambiguous, evolving problems
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Familiarity with NLP techniques like ranking models, text classification, embeddings, or information retrieval
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Excellent communication skills with the ability to explain complex technical concepts to stakeholders
OUR DATA SCIENCE STACK
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Languages: Python, SQL
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Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX
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Backend: GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery
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AI Models: OpenAI, Claude, Perplexity, Gemini, Llama, etc.
BONUS POINTS
- Contributions to…