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Artificial Intelligence Engineer
Software Engineering · Full-time
Singapore
Posted on Oct 15, 2026
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.