About the Job The Lead Engineer, Embedded Systems & Hardware will be responsible for end-to-end embedded system architecture and firmware development for a next-generation, real-time audio-capable consumer hardware product. This role includes ownership of low-power microcontroller firmware, audio integration, wireless connectivity, OTA infrastructure, and hardware bring-up. The engineer will collaborate closely with cross-functional teams across software, product, AI/ML, and third-party manufacturing partners. The ideal candidate brings a track record of shipping resource-constrained, connected, battery-powered devices and is confident working across both firmware and hardware domains. Responsibilities Own firmware architecture and implementation across two hardware platforms Integrate and optimize real-time audio processing pipelines and wake mechanisms Implement secure OTA update flows with rollback support and telemetry Lead hardware bring-up, debugging, and factory test firmware development Review schematics, manage power budgets, and advise on component placement and thermal constraints Support pre-certification efforts and collaborate with compliance consultants and EMS/ODM vendors Contribute to roadmap planning and architectural trade-offs across product development phases Qualifications 5+ years of experience in embedded systems and firmware development Hands-on experience with microcontroller platforms (e.g., ESP32, STM32) and/or Linux-class boards (e.g., Raspberry Pi Zero, NXP i.MX) Proficiency in C/C++ and real-time programming (RTOS or FreeRTOS) Experience with audio input/output integration (I²S, PDM, or similar) and DSP optimization Demonstrated experience building OTA systems with rollback, secure boot, and encryption Familiarity with wireless communication protocols such as BLE and Wi-Fi Prior involvement in power budget planning and battery management for mobile devices Competence in schematic/BOM review and debugging tools (oscilloscope, logic analyzer, etc.) Preferred Qualifications Experience designing firmware for audio-interactive or voice-triggered devices Familiarity with audio preprocessing libraries (e.g., WebRTC, SpeexDSP, AEC/NS/AGC) Exposure to MQTT or other device-cloud messaging protocols Understanding of manufacturing testing workflows, including test rig design and firmware flashing Participation in regulatory testing or certification processes (FCC, CE, UN38.3) Other Qualifications Strong documentation, communication, and cross-functional collaboration skills Comfort operating in fast-paced, early-stage hardware-software environments Ability to manage external vendors for manufacturing, PCB, or mechanical design Interest in privacy-preserving, edge-first product design principles Graduated from IITs/NITs/Tier 1 Colleges
About the Role We are hiring an AI Engineer specializing in LLMs & Interactive AI to own the narrative engine, content generation, safety/moderation systems, and personalization logic for a next-generation consumer AI product. The role focuses on building lightweight, optimized language models that generate safe, structured, and engaging interactions, deployable on both edge devices and the cloud. Responsibilities Design and implement lightweight LLM pipelines (Phi-2, TinyLLaMA, Mistral-small, etc.) for structured, interactive outputs. Build branching narrative/interaction flows with deterministic continuation and constrained decoding. Develop moderation and safety layers : rule-based filters, toxicity detection (Detoxify), and fallback to external moderation APIs (e.g., GPT/Claude). Apply content filtering and vocabulary controls to enforce safe, compliant outputs. Implement heuristics-based personalization and progress tracking for adaptive experiences. Optimize models for offline-first inference (quantization, ONNX, GGUF/ggml) with cloud fallback when needed. Build internal tools for prompt/template management, content testing, and moderation review. Work closely with the Speech AI Engineer to integrate text generation ↔ voice pipeline seamlessly. Define observability metrics (latency, generation success, moderation outcomes). Qualifications 5+ years of professional experience in applied AI/NLP, with at least 3 years focused on LLMs or conversational AI . Strong background in language models : fine-tuning, LoRA, adapter methods, prompt engineering. Proficiency in PyTorch ; experience serving models with FastAPI/Docker . Experience with edge optimization : quantization, batching, caching. Knowledge of structured AI outputs (JSON schemas, branching graphs). Hands-on with content moderation systems and multi-layer safety approaches. Understanding of privacy and compliance requirements for consumer AI apps. Nice to Have Experience with dialogue systems or conversational assistants. Exposure to personalization/recommendation systems . Familiarity with educational/narrative applications (general, not product-specific). Graduated from IITs/NITs/Tier 1 Colleges