{"id":2919424,"url":"https://alion.io/job/aikit-digital-senior-mobile-engineer-iosandroid-realtime-ai","title":"Senior Mobile Engineer – iOS/Android, Realtime AI","company":{"id":4452488,"name":"AIKIT Digital","domain":"aikitdigital.com","url":"https://alion.io/company/aikit-digital","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Mobile","role_family":"Mobile","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":70000,"max_usd":208000,"period":"year","method":"global_role_seniority_cell","sample_n":514},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AVFoundation","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Core ML","optional":false},{"name":"GCD","optional":false},{"name":"gRPC","optional":false},{"name":"Jetpack Compose","optional":false},{"name":"Kotlin","optional":false},{"name":"Kotlin Coroutines","optional":false},{"name":"Llama","optional":false},{"name":"LLM","optional":false},{"name":"MediaPipe","optional":false},{"name":"Multimodal AI","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"Speech Recognition","optional":false},{"name":"Swift","optional":false},{"name":"SwiftUI","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"UIKit","optional":false},{"name":"WebRTC","optional":false},{"name":"WebSockets","optional":false},{"name":"Wi-Fi","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"FAISS","optional":true},{"name":"FastAPI","optional":true},{"name":"GCP","optional":true},{"name":"JavaScript","optional":true},{"name":"LiteRT","optional":true},{"name":"Metal","optional":true},{"name":"Node JS","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Pinecone","optional":true},{"name":"Python","optional":true},{"name":"RAG","optional":true},{"name":"TensorFlow","optional":true},{"name":"TFLite","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true},{"name":"Whisper","optional":true}],"status":"live","first_seen_at":"2026-10-20T10:37:12Z","employer_posted_date":null,"last_verified_at":"2026-10-20T10:37:12Z","board_verified":false,"closed_at":null,"days_open":9,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":9},"description":"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. \nWhat you’ll doOwn end-to-end development of a companion mobile app that interfaces with RayBan Meta smart glasses via Meta’s Glasses SDK \nImplement 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) \nBuild voice-first UX: wakeword handoff, push-to-talk flows, VAD/ASR/TTS, earcons, and low-latency audio playback on openear speakers \nIntegrate 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 \nHandle transport and connectivity: Bluetooth LE control channels, WiFi/WiFi Direct media streaming, reconnect logic, and state machines for device pairing and session lifecycles \nDesign resilient, observable pipelines with backpressure, retries, offline fallbacks, and graceful degradation when thermals, bandwidth, or permissions change \nCollaborate with product/design on voice-first interaction patterns; run user tests; instrument metrics for latency, accuracy, and task completion \nEstablish mobile CI/CD, automated testing (unit/integration/BT device in the loop), crash/error analytics, and release processes \nChampion privacy by design and compliance with platform and bystander safety policies \n\nRequirementsMinimum qualifications5+ years professional mobile engineering experience, shipping native apps at scale on iOS or Android (preferably both) \n\nDeep proficiency in: \niOS: Swift, SwiftUI/UIKit, AVFoundation, CoreBluetooth, CoreMotion, background modes, concurrency (GCD/AsyncAwait), audio units \n\nAndroid: Kotlin, Jetpack Compose/Views, Bluetooth/BLE, Camera/Media, Foreground services, Coroutines/Flow \n\nHandson with realtime media pipelines and streaming: audio capture/playback, echo cancellation, noise suppression, lipsync/latency budgeting, WebSockets/gRPC/WebRTC, codecs (Opus/AAC/PCM) \n\nSolid networking and systems skills: state machines, threading, buffering, backpressure, power/thermal profiling, and debugging on constrained devices \nExperience integrating cloud AI services (LLM/ASR/TTS) and handling streaming inference results in the UI \nStrong product sense for voice-first UX and accessibility in eyes-up, hands-free contexts \nExcellent communication; comfortable working with early/preview SDKs and ambiguous requirements \nPreferred qualifications\nPrior 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 \nOndevice ML on phone: Core ML/Metal/Accelerate (iOS), MediaPipe/TFLite/NNAPI/GPU delegates (Android), ONNX Runtime Mobile \nMultimodal AI integration: experience with Llamafamily models, Whisper/Seamless/other ASR, TTS providers, prompt and latency optimization, partial results/streaming UX \nBLE expertise: GATT design, connection strategies, MTU/throughput tuning, coexistence with WiFi transport, device provisioning, and firmware update flows \nWebRTC for low-latency A/V; adaptive bitrate, jitter buffers, AEC/VAD tuning \nBackend exposure sufficient to move fast with AI \nPython or Node.js for inference gateways (FastAPI/Express), WebSocket servers, request fanout, and token streaming \nDeploying model servers (Triton, vLLM) and vector/RAG stacks (FAISS/Pinecone), observability (OpenTelemetry), and autoscaling on AWS/GCP/Azure \nSecurity and privacy: keychain/keystore, secure BLE pairing, PII handling, consent UX, regional data controls \nQA for hardwareintheloop: writing automated tests that exercise glasses events (connect, capture, LED state, battery, IMU), and performance tests for end-to-end latency \n\nOriginally posted on Himalayas","description_format":"text","description_chars":4305,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence"],"lifecycle":[{"event":"open","at":"2026-10-20T11:32:00Z"}],"visa":[],"liveness":{"score":79,"band":"hot","label":"Hiring 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