Role overview
**AI / Machine Learning Engineer – Agentic AI & LLM Systems**
We’re partnered with a pioneering AI organisation pushing the boundaries of
**Agentic AI**
— building systems where
**LLMs reason, act, and collaborate autonomously**
to drive real-world outcomes.
Designing the frameworks, tools, and data loops that allow intelligent agents to think, plan, and improve themselves — transforming raw model power into adaptive, high-performing AI systems.
**What You’ll Do:**
* **Build Agentic Systems**
– Develop and optimise LLM-based agents that can reason, plan, and execute multi-step tasks autonomously.
* **Enhance LLM Reasoning**
– Apply reinforcement learning, tool use, and reflection techniques to strengthen decision-making and contextual understanding.
* **Design Scalable Frameworks**
– Create data pipelines, annotation tools, and evaluation flywheels that accelerate model iteration and feedback loops.
* **Collaborate with Research Teams**
– Translate experimental findings into production-grade systems that extend the autonomy and reliability of agents.
* **Run Experiments End-to-End**
– Own your compute environment (e.g. Jupyter, Colab, Databricks) and iterate on large-scale LLM training and evaluation.
**What You’ll Bring:**
* 4+ years’ experience in
**Machine Learning or AI**
, with exposure to
**LLM agent systems**
, tool-use frameworks, or generative AI.
* Advanced proficiency in
**Python**
and ML frameworks such as
**PyTorch**
or
**TensorFlow**
.
* Hands-on experience developing or fine-tuning
**LLaMA**
,
**GPT**
, or similar foundation models.
* Understanding of
**agentic architectures**
, chain-of-thought reasoning, and memory/reflection mechanisms.
* Proven ability to debug, optimise, and scale ML experiments and compute pipelines.
* MSc or PhD in
**AI, Computer Science, or related field**
.
Please apply for immediate consideration.