Artificial Intelligence Engineer

Shokz; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Shokz is seeking an AI Engineer to help build and optimize speech models (ASR, TTS) and pipelines for wearable devices. You will work across requirements, design, debugging, and iteration to improve scenario performance and response stability.

Responsibilities include on-device deployment, quantization, and inference optimization, plus collaboration with product, algorithm, system and testing teams to drive data-driven improvements and robust experiences.

Qualifications

• Solid understanding of DL architectures (Transformer/Conformer/BERT) and ASR/LLM tech basics.
• Strong programming skills in Python, C++, or Java.
• Experience with model deployment and on-device inference concepts.
• Familiarity with AI app development approaches (RAG, prompts, orchestration).
• Knowledge of ONNX, TFLite, or similar frameworks is a plus.
• Able to diagnose common performance, latency and reliability issues.

Responsibilities

• Contribute to building and optimizing speech models (ASR, TTS) and pipelines.
• Participate in end-to-end AI feature development for wearables, including design and testing.
• Engage in on-device model deployment, quantization, and performance tuning.
• Support AI agents with capabilities like task planning, tool invocation, and memory.
• Collaborate with product, algorithm, system, and test teams on data analysis and evaluation.
• Contribute to engineering best practices including logging, release management, and stability.

Skills

Deep learning

Python

C++

Java

RAG

On-device AI

Education

Bachelor’s degree or above in Computer Science / AI / Software Engineering

Tools

ONNX

TFLite

NCNN

MNN

ONNXRuntime

Job description

• Contribute to building and optimizing speech model (ASR, TTS etc.) and application pipelines (Prompt, RAG, tool calling, service orchestration) to improve scenario performance and response stability.


• Participate in end to end development and integration of AI features for wearables, covering requirement decomposition, solution design, joint debugging/testing, and version iteration.


• Engage in on-device model deployment and performance optimization, including model conversion, quantization compression, inference acceleration, and resource tuning (latency, memory, power consumption).


• Support the engineering development of AI Agents, implementing capabilities such as task planning, tool invocation, and multi-turn memory in device scenarios.


• Collaborate with product, algorithm, system, and testing teams on data analysis, effect evaluation, issue diagnosis, and closed-loop improvement.


• Contribute to engineering best practices, including evaluation baselines, logging/monitoring, graceful fallback, release management, and stability assurance mechanisms.

Requirements

• Bachelor’s degree or above in Computer Science, Artificial Intelligence, Software Engineering, Electronic Information, Automation, or related fields.


• Solid understanding of Deep Learning architectures (Transformer, Conformer, RNN-T, BERT) and familiarity with mainstream ASR/speech technologies or LLM frameworks.


• Solid programming skills with proficiency in at least one of Python, C++, or Java.


• Familiar with at least one AI application development approach (e.g., large-model API integration, RAG, Prompt engineering, workflow orchestration).


• Interest in on-device AI engineering; familiarity with any of ONNX, TFLite, NCNN, MNN, or ONNXRuntime is a plus.


• Basic engineering debugging capabilities, able to independently diagnose common issues (performance fluctuations, API timeouts, resource anomalies, stability problems).