Design and develop end-to-end machine learning pipelines for real-time inference across edge and cloud.
•    Implement and train ML models for:
o    Behavior prediction based on device interaction patterns.
o    Emotion recognition using audio signal processing and ML.
o    Environmental and biometric sensor data fusion for user intent estimation.
•    Work closely with product teams to create personalized automation routines that adapt over time.
•    Build and maintain scalable data ingestion and labeling pipelines integrating IoT, wearables, weather APIs, and indoor sensors.
•    Collaborate with front-end and device teams to optimize model delivery across platforms (mobile/web/embedded).
•    Contribute to SyncOS’s learning engine — reinforcement learning, habit inference, and anomaly detection modules.
•    Architect and implement agentic solutions using LLMs integrated via LangGraph and LangChain.
•    Design custom chains, tools, and memory integrations to support interactive AI companions.
•    Define and lead A/B testing strategies for AI-driven features.