Software Engineer - Apps & Device Integrations

About the role

About the Role

Human-centered physical intelligence starts with perceiving the physical world and the people in it. That means our software runs against real hardware — in real homes and workplaces, on diverse real-world tasks, producing continuous multimodal signal that our AI systems process in real time and learn from afterward.

We're looking for an experienced engineer who has shipped native apps on both iOS and Android to own that surface end to end: our mobile and companion apps, the integrations with the devices we run on, the capture pipelines that feed our data engine, and the platform layer everything else builds on. The work spans mobile, hardware, real-time systems, and AI, and it rewards someone who is comfortable moving between them.

What You'll Do

Own our iOS and Android apps end to end — architecture, implementation, quality, performance, and release management through App Store and Google Play — capturing real-world signal at scale and delivering real-time, AI-powered experiences wherever our hardware operates.

Build the capture and upload path for large-scale data collection across many devices and participants.

Build companion clients for other form factors, from embedded and wearable displays to home hubs and operator consoles, where a phone app isn't the right interface.

Own the layer where our software meets hardware — SDKs, connectivity, capture and streaming, command and control — and the reliability work that makes it feel effortless.

Move real-world signal from hardware to our real-time AI backend and back again under tight latency budgets, and keep it working when conditions aren't ideal.

Shape the platform and SDK surface so new devices, capabilities, models, and services can plug in without a rewrite.

Set the bar for engineering quality — architecture, testing, performance, and reliability in real-world conditions.

What We're Looking For

8+ years of professional software engineering experience, with a track record of shipping production mobile applications and the systems behind them at scale.

You have launched native apps on both iOS and Android and owned them through the full lifecycle — architecture, implementation, App Store and Google Play submission and review, staged rollout, and production monitoring — without a separate platform team to hand off to.

Practical experience with AI-native development — you use AI coding tools and agents as a core part of your daily workflow to move faster without sacrificing quality, and you have strong judgment about when to lean on them and when not to.

Hands-on experience integrating physical hardware — you've shipped software that captures and streams real-world signal off a device, or controls one.

Sound judgment about real-time systems in the field and what to do when the ideal case doesn't hold.

Startup DNA: high ownership, comfort with ambiguity, and the judgment to make pragmatic calls on a small, fast-moving team.

Stack & Skills

Fluent

Native iOS — Swift, SwiftUI and UIKit, Xcode, and the platform layer underneath: AVFoundation and media capture, background execution, permissions and entitlements, Core Bluetooth, and working within power, thermal, and memory limits

Native Android — Kotlin, Jetpack Compose, Android Studio, and the platform layer underneath: CameraX and MediaCodec, foreground services and WorkManager, runtime permissions, Bluetooth LE, and OEM-specific power management

Mobile release engineering — CI/CD with Fastlane, Xcode Cloud, Bitrise, or GitHub Actions; code signing, provisioning profiles, and Play App Signing; TestFlight and Play internal, closed, and open testing tracks; phased and staged rollouts; crash and performance monitoring with Crashlytics, Sentry, or Firebase Performance; and App Store Review Guidelines and Play policy compliance, including privacy manifests and Data safety declarations

Companion form factors — wearable, embedded, hub, or headless devices, and the constraints that come with them

TypeScript, and React or React Native — our platform and tooling are TypeScript-first

Real-time transports — WebRTC, WebSockets, REST — and the ability to debug all three under load

Capture and streaming pipelines for time-synchronized multimodal data

Testing on real hardware in real-world conditions

Working knowledge

Backend services and pub/sub architectures

Cloud infrastructure (AWS or GCP), containers, and observability for real-time systems

On-device inference and model runtimes — Core ML, TFLite, ONNX, or similar

Media codecs and their tradeoffs (H.264/HEVC/AV1, Opus) under jitter, packet loss, and adaptive bitrate

Device connectivity and messaging protocols — Matter, Thread, MQTT, or similar — and coordinating many devices at once

Home automation ecosystems — HomeKit, Google Home, SmartThings, or Home Assistant integrations

Embedded Linux and RTOS environments — cross-compilation, OTA updates, and provisioning devices in the field

Bonus

Experience on an emerging device platform — before mature tooling, docs, and abstractions

BLE and peripheral protocols, firmware-adjacent debugging, hardware bring-up

Robotics middleware and control — ROS 2 or similar, real-time control loops, safety interlocks, and fleet tooling

Teleoperation and robot operator interfaces — low-latency video plus control streams, mission control, and live status for one robot or a fleet

Building tooling for robot learning research — teleoperation rigs, demonstration capture, or evaluation harnesses for a robotics lab or policy-learning team

Robotics data formats and platform SDKs — ROS bags, MCAP, Foxglove; Boston Dynamics Spot, Unitree, Universal Robots, or similar

Real-time perception pipelines and sensor fusion

Data-pipeline work — moving large volumes of multimodal capture into storage and training systems

Building or maintaining public SDKs or developer platforms

Shipping software used in the physical world, where failure has real consequences

Who You'll Work With

You'll be working with a tightly knit team that has pioneered frontier AI research, shipped tens of millions of devices, scaled infrastructure used by millions every day, and defined how people and machines interact in the physical world. They've done it at Meta, Amazon, Microsoft, and Valve.

Why Join

Early role at a funded startup founded by people who built some of the most advanced AI, systems, and hardware programs in the industry.

Build the layer that connects people to physical intelligence in their homes and workplaces, across every device we run on.

You'll work across the whole stack: applications, platform, AI, and real-time infrastructure.

Small team, exceptional peers, no bureaucracy.

Compensation: Competitive salary plus meaningful early-stage equity and benefits.

All applicants must be legally authorized to work in the United States. Noösphere will consider sponsorship of qualified candidates for employment visa status where required. Noösphere is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.