Artificial Intelligence Engineer

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. #J-18808-Ljbffr