Lead AI Engineer

4 days ago

bangalore district, India PetYosa Full time

📍 Bangalore | Full-Time | ₹20–30 LPA | Min. 4 Years of Experience | Hands-On Role We are building a new kind of intelligence platform that sits at the intersection of health, behaviour, wearables, and real-time decision systems. Our data pipeline captures 60,000+ data points per pet per day across motion, GPS, audio, health logs, and behavioural events. We are looking for a founding AI engineer who can own the end-to-end AI architecture — not just build models, but productionize them at scale with real-world impact. What You’ll Build You’ll be responsible for architecting and shipping: Full-stack AI/ML pipelines to handle real-time multimodal pet data Time-series models to detect early illness, restlessness, aggression, and sleep anomalies Smart nudges and personalised pet recommendations (movement, health, care) Behavioural clustering and risk scoring engines (for insurance, hosts, vet dashboards) Embedding models powering our internal PetAI assistant Data architecture for structured + unstructured pet telemetry and app activity Future integrations: on-device/edge inference for our smart collar Who Uses Your Work Pet parents (daily insights and warnings) Vets (medical context and pre-visit summaries) Groomers and hosts (temperament tagging) Internal AI assistant (PetAI) Ops and support teams (incident prediction) Founders and BI teams (trend dashboards, retention analytics) Future insurance and ecosystem partners (risk engines) What We’re Looking For Minimum 3 years of hands-on experience in ML/AI engineering Strong foundation in time-series modeling, signal processing, or real-time inference Experience with tools like PyTorch, TensorFlow, Scikit-learn Knowledge of embeddings, retrieval pipelines, vector DBs Data infrastructure fluency: streaming (Kafka), orchestration (Airflow), DBs (Postgres) Ability to build for scale, not just hack demos Prior experience working with IoT or health/behavior data is a strong plus Bonus: Edge ML, on-device inference, LLM integrations Must be comfortable working independently in a fast-moving startup environment

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