ML Research Engineer - Member of Technical Staff

About the role

Callosum is building an infrastructure layer that orchestrates heterogeneous models and hardware to improve AI system performance and cost. This role focuses on developing a principled, evidence-based method for building agentic systems at scale. You will design experiments to understand system failures and build the evaluation infrastructure necessary to drive future design decisions.

Responsibilities

• Design and run experiments that isolate why agentic systems fail across behaviour, traces and activations.
• Attack core research themes including context and memory management, agent steering, task decomposition, and continual learning.
• Build durable agent analysis and evaluation infrastructure such as observability, behaviour analysis, and auditing tools.
• Publish research findings, methods, and discoveries as both company assets and public evidence.
• Work across team boundaries to design systems for specific applications or invent novel model and agent architectures.

Required skills

• LLMs
• Agentic systems
• Experimental design
• Software engineering

Nice to have

• RL
• Post-training
• Multi-agent systems
• Planning
• Program synthesis
• SGLang
• vLLM
• Distributed systems

Qualifications

• Evidence of ability to run independent research
• Deep hands-on experience with LLMs in agentic settings
• Strong engineering background
• Strong communication skills

Benefits

• Competitive salary
• Equity
• Private healthcare
• Visa sponsorship
• Relocation benefits

About the Company

Callosum is an Intelligent Systems Company building the software orchestration layer that unifies heterogeneous compute across the full stack. They are based in London and focus on co-evolving models, workflows, and silicon to deliver inference tailored to every workload.