Research AI Director

About the Role

The Research AI Director is a senior scientific leadership position responsible for shaping and executing Multiverse Computing's AI research strategy. Reporting directly to the Chief Scientific Officer, you will lead a high-calibre, multidisciplinary AI research organisation, drive world-class LLM and AI development from research through to production, and bridge the best of academia and industry within a fast-moving deep-tech environment.

This role demands a rare combination: deep hands-on expertise in large language model development, a strong academic publication record, proven success managing and scaling AI engineering teams in both research and commercial settings, and the strategic vision to align cutting-edge science with real-world product impact. You will be a key voice in the company’s AI direction and a trusted partner to the CSO.

Key Responsibilities

• Strategic AI Research Leadership

  • Define and own the multi-year AI research roadmap, spanning foundation models, model compression, alignment, and applied AI ensuring alignment with company strategy and product priorities.

  • Partner closely with the CSO to translate scientific vision into concrete, deliverable research programmes with measurable milestones.

  • Identify emerging trends in LLMs, multimodal AI, and efficient inference, and position Multiverse at the frontier of applied AI research.

  • Represent Multiverse Computing at top-tier international conferences (NeurIPS, ICML, ACL, ICLR) and scientific advisory forums.

• Team Leadership & People Management

  • Lead, mentor, and scale a diverse AI research organisation of researchers, ML engineers, software engineers, and applied scientists — maintaining a culture of scientific excellence, collaboration, and ownership.

  • Set clear performance expectations, conduct rigorous reviews, and support the professional development and career growth of team members at all levels.

  • Recruit and retain world-class AI talent across both academic and industry profiles, working with HR and the CSO to build a compelling research environment.

  • Coach team leads and senior researchers, fostering technical depth alongside engineering rigour.

• LLM Development & Research Delivery

  • Own the end-to-end LLM development lifecycle: pretraining, fine-tuning, alignment (RLHF/DPO), evaluation, and production deployment — bridging research prototypes to scalable systems.

  • Oversee the planning and execution of concurrent AI research projects, ensuring high scientific quality, reproducibility, and on-time delivery.

  • Establish robust KPIs, publication targets, and reporting frameworks to track research progress, model performance, IP generation, and product handoffs.

  • Ensure seamless knowledge transfer between research and product/engineering teams, translating scientific breakthroughs into deployable technology.

• Cross-functional & External Collaboration

  • Collaborate with Product, Engineering, and Business Development to ensure AI research outputs are commercially relevant and technically integrable.

  • Build and maintain relationships with leading academic institutions, national laboratories, and AI research consortia.

  • Manage external collaborations including university partnerships, EU-funded research projects, and industrial consortia.

  • Support pre-sales and strategic customer engagements by articulating AI research capabilities and roadmap to both technical and executive audiences.

  • Contribute to grant applications, scientific publications, patents, and white papers that reinforce Multiverse’s intellectual leadership.

Qualifications & Experience

• PhD in Computer Science, Machine Learning, Mathematics, or a closely related field, with a strong peer-reviewed publication record in AI/ML at top venues (NeurIPS, ICML, ACL, ICLR, EMNLP, or equivalent).

• 8+ years of post-doctoral or industry research experience, with at least 2 years in a senior AI research leadership or management role.

• Deep, proven expertise in large language model (LLM) development: pretraining, fine-tuning, RLHF/DPO alignment, evaluation, and deployment at scale.

• Demonstrated track record of managing and scaling AI research or engineering teams in both academic and commercial/industrial environments.

• Experience spanning both academia and industry: ability to operate with academic rigour (publications, reproducibility, peer review) and industrial discipline (delivery timelines, product integration, stakeholder communication).

• Hands-on experience with distributed training infrastructure: multi-GPU/multi-node clusters, frameworks such as Megatron-LM, DeepSpeed, or FSDP, and performance profiling at scale.

• Strong strategic thinking with the ability to set direction, prioritise across competing initiatives, and communicate complex research to non-specialist audiences.

• Excellent interpersonal and stakeholder management skills — credible with both world-class scientists and C-suite executives.

Nice to Have

• Familiarity with quantum computing, tensor networks, or quantum-inspired optimisation methods — valuable given Multiverse’s quantum heritage, but not a barrier to entry.

• Track record of securing competitive research funding (EU Horizon, national grants, or equivalent programmes).

• Background advising enterprise clients on AI research strategy or roadmap.

Perks & Benefits

• Indefinite contract

• Equal pay guaranteed.

• Variable performance bonus.

• Signing bonus.

• We offer work visa sponsorship (If applicable).

• Relocation package (if applicable).

• Private health insurance.

• Eligibility for educational budget according to internal policy.

• Hybrid opportunity.

• Flexible working hours.

• Language classes and discounted lunch options

• Working in a high paced environment, working on cutting edge technologies.

• Career plan. Opportunity to learn and teach.