AI Engineer

Engineering SG

About your role

You'll build the agent and the models behind it, from tool and skill design to fine-tuning and serving open-weight models on customer premises.

Agent engineering

Design and build agent tools and process skills that let the agent plan scans, generate robot programs and resolve motion errors.Build multi-model orchestration, routing tasks across large and small models to balance accuracy, latency and token cost.Own context engineering: prompts, tool schemas, and retrieval over process knowledge.

Models

Fine-tune open-weight large language models and vision-language models (supervised fine-tuning, Low-Rank Adaptation and its quantised variant) on domain data.Distill large teacher models into small, deployable models.Serve and optimise models on graphics processing units for on-premises and airgapped deployments (quantisation, batching, vLLM or similar).

Evaluation and reliability

Build deterministic evaluation harnesses and benchmark suites; track regressions across model and agent versions.Own model and dataset versioning, experiment tracking and release workflows.Build logging and tracing for agent runs to support debugging and reliability.Curate training and evaluation datasets for agent and model development.

Requirements

2–5 years building machine learning or large language model systems that reached production.

Strong Python and solid engineering practice (testing, Git, code review, application programming interfaces).

Hands-on agent development: tool and function calling, structured outputs, prompt and context engineering.

Hands-on fine-tuning of open-weight models (PyTorch, Hugging Face, parameter-efficient fine-tuning libraries).

Experience designing evaluations that measure model or agent quality objectively.

Experience deploying models (Docker, graphics processing unit inference, cloud platforms).

Good to have

Multi-agent or subagent architectures.

Distillation, quantisation, or on-premises and airgapped deployment.

Vision-language models, 3D point clouds, or computer vision.

Robotics, Robot Operating System, motion planning or industrial automation.

Agile development with Jira.

A degree in computer science or a related field is welcome but not required. We care about what you've built.

What success looks like

3 months: shipped a new agent tool or skill to production, with an evaluation covering it.

6 months: own a fine-tuned or distilled model in the evaluation and release pipeline.

12 months: a self-hosted model you built is running in a customer deployment.