# AI Phone - On-device AI / ML Systems Engineer at Bjakcareer

> Hybrid · United Kingdom · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Abjakcareer%3Ab3c8a2c9-e27e-484f-a3f9-1a25e40174da (read 2026-11-05).

## Facts (observed)

- Company: [Bjakcareer](https://alderhq.app/companies/bjakcareer)
- Location text: United Kingdom
- Where it can be done from (inferred): Hybrid · United Kingdom (evidence: "Location: United Kingdom")
- Posted: 2026-11-04 (2 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-04
- Reposted: 1 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/bjakcareer/b3c8a2c9-e27e-484f-a3f9-1a25e40174da
- Skills listed (inferred): Python, C++, Android, TensorFlow, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (United Kingdom, n 22): p25 £88k, median £134k, p75 £296k

## Description (the employer's text)

### About

We are reimagining the phone. AI phones need to be proactive, intuitive, intelligent and low cost. This is a mission critical for rest of the world to adopt intelligence.

There are over 5 billion people using everyday applications such as email, messaging, notes, tasks, and calendars, yet most are not AI-native. Our mission is to build proactive applications and devices that bring intelligence into daily conversations, coordination and workflows, with minimal prompting.

### Responsibilities

Evaluate suitable open-weight and commercially available models for on-device execution.

Benchmark model performance on target mobile hardware.

Integrate models into Android applications and system services.

Optimize inference latency, memory consumption and power usage.

Evaluate quantization, compression and model distillation techniques.

Work with CPU, GPU and NPU acceleration.

Evaluate local model capabilities for different workflows.

Build hybrid local/cloud model routing mechanisms.

Identify which tasks can be handled locally and which require cloud inference.

Work with AI agent engineers to integrate local models into the agent runtime.

### Requirements

Strong ML systems or inference engineering experience.

Experience deploying and optimizing models.

Strong Python and C++ skills.

Understanding of neural network inference.

Experience with model quantization and performance optimization.

Understanding of hardware constraints and inference benchmarks.

### Nice to have

Experience with on-device LLMs.

Qualcomm QNN, MediaTek NeuroPilot or similar acceleration frameworks.

ONNX Runtime, LiteRT, TensorFlow Lite or ExecuTorch.

Android NDK.

Mobile or edge AI deployment.

Multimodal model optimization.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Abjakcareer%3Ab3c8a2c9-e27e-484f-a3f9-1a25e40174da and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.