Senior Mobile Engineer – iOS/Android, Realtime AI

This is a remote position.
We’re hiring a Senior Engineer to build production mobile apps and services that integrate with Meta’s Glasses SDK for RayBan Meta smart glasses. You’ll design and ship hands-free, voice-first, vision-enabled experiences that span the glasses, a companion iOS/Android app, and cloud AI. This is a highly cross-functional role at the intersection of mobile, real-time audio/video, Bluetooth/WiFi transport, and multimodal AI.
What you’ll do
Own end-to-end development of a companion mobile app that interfaces with RayBan Meta smart glasses via Meta’s Glasses SDK

Implement reliable capture and streaming pipelines for camera preview frames, stills, and multichannel audio, with strict attention to latency, battery, and privacy indicators (camera LED, permissions)

Build voice-first UX: wakeword handoff, push-to-talk flows, VAD/ASR/TTS, earcons, and low-latency audio playback on openear speakers

Integrate on-phone computer vision and speech models (Core ML, MediaPipe, ONNX Runtime, NNAPI) and orchestrate cloud inference for multimodal LLMs (e.g., Llama 3family vision/voice) via streaming APIs

Handle transport and connectivity: Bluetooth LE control channels, WiFi/WiFi Direct media streaming, reconnect logic, and state machines for device pairing and session lifecycles

Design resilient, observable pipelines with backpressure, retries, offline fallbacks, and graceful degradation when thermals, bandwidth, or permissions change

Collaborate with product/design on voice-first interaction patterns; run user tests; instrument metrics for latency, accuracy, and task completion

Establish mobile CI/CD, automated testing (unit/integration/BT device in the loop), crash/error analytics, and release processes

Champion privacy by design and compliance with platform and bystander safety policies

Requirements
Minimum qualifications
5+ years professional mobile engineering experience, shipping native apps at scale on iOS or Android (preferably both)

Deep proficiency in:
iOS: Swift, SwiftUI/UIKit, AVFoundation, CoreBluetooth, CoreMotion, background modes, concurrency (GCD/AsyncAwait), audio units

Android: Kotlin, Jetpack Compose/Views, Bluetooth/BLE, Camera/Media, Foreground services, Coroutines/Flow

Handson with realtime media pipelines and streaming: audio capture/playback, echo cancellation, noise suppression, lipsync/latency budgeting, WebSockets/gRPC/WebRTC, codecs (Opus/AAC/PCM)

Solid networking and systems skills: state machines, threading, buffering, backpressure, power/thermal profiling, and debugging on constrained devices

Experience integrating cloud AI services (LLM/ASR/TTS) and handling streaming inference results in the UI

Strong product sense for voice-first UX and accessibility in eyes-up, hands-free contexts

Excellent communication; comfortable working with early/preview SDKs and ambiguous requirements

Preferred qualifications
Prior work with Meta’s Glasses SDK (RayBan Meta) or similar wearables (Apple Watch/visionOS audio, Snap Spectacles, Bose Frames) – if you don’t have this experience, it is fine, provided that you are willing to learn the Meta Glasses SDK quickly

Ondevice ML on phone: Core ML/Metal/Accelerate (iOS), MediaPipe/TFLite/NNAPI/GPU delegates (Android), ONNX Runtime Mobile

Multimodal AI integration: experience with Llamafamily models, Whisper/Seamless/other ASR, TTS providers, prompt and latency optimization, partial results/streaming UX

BLE expertise: GATT design, connection strategies, MTU/throughput tuning, coexistence with WiFi transport, device provisioning, and firmware update flows

WebRTC for low-latency A/V; adaptive bitrate, jitter buffers, AEC/VAD tuning

Backend exposure sufficient to move fast with AI

Python or Node.js for inference gateways (FastAPI/Express), WebSocket servers, request fanout, and token streaming

Deploying model servers (Triton, vLLM) and vector/RAG stacks (FAISS/Pinecone), observability (OpenTelemetry), and autoscaling on AWS/GCP/Azure

Security and privacy: keychain/keystore, secure BLE pairing, PII handling, consent UX, regional data controls

QA for hardwareintheloop: writing automated tests that exercise glasses events (connect, capture, LED state, battery, IMU), and performance tests for end-to-end latency

Originally posted on Himalayas