Senior Audio and Voice Engineer

Responsibilities

• Leads the architecture, design, and deployment of Voice AI capabilities on edge devices, including STT, TTS, Wake Word detection, speaker diarization, and voice command pipelines.
• Drives end-to-end audio signal chains, from microphone input through hardware drivers, DSP, AI inference, and application-level consumption.
• Owns latency, accuracy, robustness, and power efficiency targets for on-device speech and audio systems.
• Defines and executes technology roadmaps for edge AI, speech models, and audio platforms aligned with business goals and product strategy.
• Converts business concepts and product requirements into production‑ready Voice AI solutions, delivering MVPs using adaptive Agile methodologies.
• Implements audio hardware integration, including microphone arrays, codecs, amplifiers, beamforming hardware, and acoustic design alignment.
• Drives audio fine‑tuning and calibration, including gain staging, AEC, noise suppression, echo cancellation, and far‑field optimization.
• Collaborates with hardware, silicon, and firmware teams to ensure co‑design of audio HW, DSP, and AI workloads.
• Leads on‑device ML model integration for edge constraints.
• Establishes standards and tooling for continuous model evaluation, deployment, and rollback on edge platforms.
• Designs and builds secure, scalable Voice AI platforms, ensuring protection of user data with on‑device processing and privacy‑by‑design principles.
• Defines and automates build, test, validation, and deployment pipelines for embedded and edge AI software.

• Bachelor’s or Graduate degree in Computer Science, Electrical Engineering, Software Engineering, Machine Learning, Signal Processing, or a related discipline, or equivalent demonstrated experience.
• Typically 10+ years of experience in software engineering, embedded systems, audio processing, or platform architecture.
• Proven experience delivering production Voice AI or audio systems, preferably on constrained or embedded devices.
• Programming Language certifications (C++, Python, Java, or similar).
• Embedded systems, ML, or cloud/edge architecture certifications (preferred but not required).