Project Technical Lead - AI Systems Simulation

CommonAI CIC; Cambridge; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Pension

Healthcare

Office near Cambridge train station

Job summary

CommonAI CIC is seeking a Project Technical Lead to steer the Scaling Inference simulation platform and define the technical strategy for the project. You will coordinate cross-functional workstreams bridging hardware architecture and model workloads to deliver a cohesive toolkit.

In this leadership role you will set engineering standards, guide research engineers, and ensure outputs align with the programme's strategic mission.

Qualifications

• Technical leadership experience in a research or high-growth engineering environment.
• Ability to translate complex technical concepts for diverse stakeholders.
• Advanced degree (PhD preferred) in Computer Science, Engineering, or a related field with deep domain knowledge in AI systems and hardware architecture.
• Track record of delivery, moving sophisticated technical prototypes through to production-grade, scalable systems.
• Experience with GPU optimisation, performance modelling, and the simulation of large-scale infrastructure workloads.

Responsibilities

• Technical Strategy & Vision: Own the architectural roadmap for the Scaling Inference simulation platform.
• Workstream Coordination: Manage and synchronise development efforts across hardware, software, and model workload workstreams to deliver a cohesive simulation toolkit.
• Technical Standards & Quality: Establish and enforce engineering best practices, rigorous validation methodologies, and performance standards across the team.
• Stakeholder Management: Act as the primary technical point of contact for the Scaling Inference programme, communicating progress and technical risks to senior leadership and partners.
• Mentorship & Growth: Provide technical guidance and mentorship to research engineers, fostering a culture of innovation and continuous professional development.
• Project Delivery: Lead the planning and execution of experimental cycles, ensuring the Scaling Inference Lab outputs are integrated into the core platform efficiently.
• Resource Allocation: Prioritise technical tasks and research questions to maximise programme impact on cost, performance, and energy efficiency targets.
• Documentation: Communicate findings through technical reports, internal publications, and external research outputs.

Skills

Technical leadership

Strategic communication

GPU optimisation

Performance modelling

Stakeholder management

Education

PhD preferred in CS/Engineering or related field

Job description

CommonAI is redefining deep-tech AI solutions through collaborative engineering and shared infrastructure. Working at the intersection of AI, cloud, and large-scale infrastructure, we partner with commercial, government, and research entities to accelerate AI adoption across the UK and Europe. Backed by UK Government and private funding, our team of experienced founders and engineers is building the future of AI systems.

Role

As AI models scale, understanding the real‑world impact of hardware, systems software, and architecture on performance, cost, and energy is critical. CommonAI's £70m+ Scaling Inference programme is developing a comprehensive simulation toolkit to model inference systems across the stack.

We are seeking a Project Technical Lead to spearhead this initiative. In this leadership role, you will define the technical strategy for our simulation platform, coordinating cross‑functional workstreams to bridge the gap between hardware architecture and model workloads. You will be responsible for the programme's overall technical direction, setting standards for excellence, and ensuring the research outputs align with our strategic mission.

Key Responsibilities

• Technical Strategy & Vision: Own the architectural roadmap for the Scaling Inference simulation platform, ensuring technical decisions support long‑term goals
• Workstream Coordination: Manage and synchronise development efforts across hardware, software, and model workload workstreams to deliver a cohesive simulation toolkit
• Technical Standards & Quality: Establish and enforce engineering best practices, rigorous validation methodologies, and performance standards across the team
• Stakeholder Management: Act as the primary technical point of contact for the Scaling Inference programme, communicating progress and technical risks to senior leadership and partners
• Mentorship & Growth: Provide technical guidance and mentorship to research engineers, fostering a culture of innovation and continuous professional development
• Project Delivery: Lead the planning and execution of experimental cycles, ensuring the Scaling Inference Lab outputs are integrated into the core platform efficiently
• Resource Allocation: Prioritise technical tasks and research questions to maximise programme impact on cost, performance, and energy efficiency targets
• Documentation: Communicate findings through technical reports, internal publications, and external research outputs

Requirements

• Technical Leadership: Proven experience leading technical teams or managing complex engineering projects in a research or high‑growth environment
• Strategic Communication: Ability to translate complex technical concepts for diverse stakeholders and influence technical strategy at a programme level
• Advanced degree (PhD preferred) in Computer Science, Engineering, or a related field with deep domain knowledge in AI systems and hardware architecture
• Track record of delivery, moving sophisticated technical prototypes through to production‑grade, scalable systems
• Experience with GPU optimisation, performance modelling, and the simulation of large‑scale infrastructure workloads

Desirable

• Experience managing cross‑functional teams in AI infrastructure, ML systems, or computer architecture
• Familiarity with Agile or other modern technical project management frameworks
• Knowledge of modern inference‑serving frameworks (e.g., vLLM)
• Background in statistics, operations research, or large‑scale datacenter infrastructure
• Contributions to open‑source AI or systems projects

Benefits

• High‑impact role in a rapidly growing, well‑funded organisation
• Collaborative and supportive work environment
• Competitive salary, pension, healthcare, and benefits
• Networking opportunities with leaders across tech and academia
• Vibrant office situated near to Cambridge train station

CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace.