Job Title: Senior Mobile Engineer – iOS/Android, Realtime AI

Company Name: AIKIT Digital

Job Details: RemoteFull,Time

Job Url: https://hiring.cafe/viewjob/uw23rzzpz5dmp1oo

Job Description: Posted 6mo agoSenior Mobile Engineer – iOS/Android, Realtime AI@ AIKIT DigitalView All JobsWebsiteUnited StatesRemoteFull TimeResponsibilities:Own development, Implement streaming, Build voice-firstRequirements Summary:5+ years mobile development on iOS or Android; strong Swift/Kotlin, realtime media pipelines, cloud AI services, networking, privacy and performance awareness.Technical Tools Mentioned:Swift, SwiftUI, UIKit, AVFoundation, CoreBluetooth, CoreMotion, Android, Kotlin, Jetpack Compose, WebSockets, WebRTC, ONNX Runtime, Core ML, MediaPipe, NNAPI, BLE, WiFi, Bluetooth, LLM, ASR, TTS, FastAPI, Express, WebSocket servers, Triton, vLLM, FAISS, Pinecone, OpenTelemetry
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
   
   
    
   RequirementsMinimum 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