As the Tech Lead for Structured Insights & Detection, you’ll own the algorithms and systems that turn messy, multi-channel feedback into reliable structured insights, flexible anomaly detectors, and novelty discovery—and deliver trustworthy alerts to product & CX teams. You’ll collaborate directly with engineers, directors, the CTO, and other tech leads to turn ambitious prototypes into a rock-solid product used by brands like Grubhub, Booking, Dropbox & Uber.
Company Anecdote
Anecdote is an innovative, AI-first startup revolutionizing how companies analyze customer feedback. Our AI-powered platform consolidates feedback from app reviews, support chats, surveys, and social media into a single, easily accessible space. This enables companies like Grubhub, Dropbox, Fubo, Booking.Com and Uber to derive actionable insights and deliver a better, real-time customer experience that drives sustainable growth.
We’re backed by Neo, Sukna, Race Capital, Propeller, and Wamda.
50% Build — design & ship
Structured extraction from unstructured text (and other modalities) using schema-driven pipelines, tool-use, and retrieval. Hybrid anomaly detection blending classical time-series (Prophet/statsmodels/Kats) with LLM-aware, contextful detectors (seasonality, spikes, step-changes, drift). Novelty discovery: embedding-based clustering & drift, topic surfacing, and LLM summarization of emerging themes with deduplication and evidence links. Alerting & scoring: severity/impact ranking, de-noising, suppression/cool-downs, routing, and feedback loops. 25% Architect & scale
Own reliability, latency, and cost, design online/offline eval harnesses, canarying, and SLAs. Operate GPUs/accelerators where needed. Own on-call for your area.
15% Collaborate
Pair with back-end & front-end to wire detectors/extractors into ticketing, voice, and analytics stacks (APIs, webhooks, real-time streams). Partner with PMs/CX to evolve taxonomies, schemas, and guardrails.
10% Align & showcase
Gather requirements from CX leads, demo new capabilities to execs & customers, and document impact in plain English with precision/recall, alert quality, and cost metrics.
Startup hacker mindset: you respect no boundaries, self-start from zero, and carry work from first prototype to production finish line. 🛠️ AI-native dev tools in your DNA: Cursor, v0, Claude Code (and similar) are daily drivers. 7–10 years building production ML/back-end systems; 2+ years leading while coding. Expert Python; strong back-end chops (FastAPI, gRPC, Postgres, pub/sub/streams). Hands-on with time-series analysis (decomposition, change-point, forecasting) and modern LLM approaches (prompting, tools, RAG). Fluency with at least one agent framework (ADK preferred) and building RAG pipelines. Track record translating business problems into shipped ML features—and explaining results clearly.
Remote-first freedom & flexible hours 🏠 Regular off-sites & monthly virtual game nights 🎉 Unlimited vacation (minimum 20 days encouraged) 🏝️ Learning budget for conferences, courses & books 📚 Startup equity in a rapidly growing market 💼
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