Multiverse Computing
Multiverse is a well-funded, fast-growing deep-tech company founded in 2019. We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.
With 180+ employees and growing, our team is fully multicultural and international. We deliver hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence.
Our flagship products, CompactifAI and Singularity, address critical needs across various industries:
- CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks. It enables the compression of large AI systems—such as language models—to make them significantly more efficient and portable.
- Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance, energy, manufacturing, and beyond. It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware.
You’ll be working alongside world-leading experts to develop solutions that tackle real-world challenges. We’re looking for passionate individuals eager to grow in an ethics-driven environment that values sustainability and diversity.
We’re committed to building a truly inclusive culture - come and join us.
Role Overview
The Research Director is a senior scientific leadership role responsible for shaping and executing Multiverse Computing's research strategy across both quantum computing and artificial intelligence. Reporting directly to the Chief Scientific Officer, you will lead a high-calibre, multidisciplinary research organisation, drive the translation of cutting-edge science into product-ready innovations, and represent the company in the global research community.
This role demands a rare combination: deep technical expertise spanning quantum algorithms and modern AI/ML, proven experience managing large, distributed research teams, and the commercial acumen to align research priorities with business objectives. You will be a key voice in the company's scientific direction and a trusted partner to the CSO.
Key Responsibilites
Strategic Research Leadership
• Define and own the multi-year research roadmap across quantum computing, quantum-inspired algorithms, and AI/ML, ensuring alignment with company strategy and product priorities.
• Partner closely with the CSO to translate scientific vision into concrete, deliverable research programmes.
• Identify emerging research trends and opportunities — including quantum advantage milestones, foundation model compression, and hybrid quantum-classical methods — and position Multiverse at the frontier.
• Represent Multiverse Computing at top-tier international conferences, workshops, and scientific advisory boards.
Team Leadership & People Management
• Lead, mentor, and grow a diverse, senior research organisation comprising quantum scientists, ML researchers, software engineers, and applied mathematicians.
• Set clear goals and performance expectations, conduct rigorous reviews, and cultivate a culture of scientific excellence, collaboration, and psychological safety.
• Recruit and retain world-class research talent, working with HR and the CSO to build a compelling scientific environment.
• Coach team leads and senior researchers, supporting their professional development and career progression.
Research Operations & Delivery
• Oversee the planning, execution, and delivery of concurrent research projects across quantum and AI workstreams, ensuring high scientific quality and on-time delivery.
• Establish robust KPIs, milestones, and reporting frameworks to track research progress, publication output, IP generation, and product handoffs.
• Manage research budgets, resource allocation, and external collaborations including university partnerships, EU-funded projects, and industrial consortia.
• Ensure seamless knowledge transfer between research and product/engineering teams, bridging the gap from scientific insight to deployable technology.
Cross-functional & External Collaboration
• Collaborate with Product, Engineering, and Business Development to ensure research outputs are commercially relevant and technically integrable.
• Build and maintain relationships with leading academic institutions, national laboratories, and industry partners.
• Support pre-sales and customer engagements by articulating research capabilities and roadmap to technical and executive audiences.
• Contribute to grant applications, scientific publications, patents, and white papers that strengthen Multiverse's intellectual leadership.
Qualifications & Experience
• PhD in Physics, Computer Science, Mathematics, or a closely related field with a strong publication record in quantum computing and/or AI/ML.
• 8+ years of overall experience including post-doctoral research experience, with at least 2 years in a senior research leadership or management role.
• Demonstrated expertise in both quantum computing (algorithms, tensor networks, variational methods, or quantum-inspired techniques) and modern AI/ML (deep learning, large language models, or model optimisation).
• Proven track record of leading and scaling multidisciplinary research teams of 15+ people across geographically distributed locations.
• Experience managing research portfolios in a commercial or deep-tech environment, balancing long-horizon science with near-term product delivery.
• Strong strategic thinking, with the ability to set direction, prioritise ruthlessly, and communicate complex research concepts to non-specialist audiences.
• Excellent interpersonal and stakeholder management skills — credible with both world-class scientists and C-suite executives.
Nice to have
• Experience with tensor network methods (MPS, DMRG, PEPS) and their applications to ML or optimisation.
• Familiarity with quantum hardware platforms (superconducting, photonic, neutral atom) and their current limitations.
• Track record of securing competitive research funding (EU Horizon, national grants, DARPA-equivalent programmes).
• Experience working with or advising enterprise clients on quantum or AI strategy.
Perks & Benefits
- Variable performance bonus.
- We offer work visa sponsorship (If applicable).
- Relocation package (if applicable).
- Private health insurance.
- Eligibility for educational budget according to internal policy.
- Language classes and discounted lunch options
- A high-performance, collaborative environment, operating at pace on cutting-edge technologies
- Career plan. Opportunity to learn and teach.
As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The emergence of senior scientific leaders specializing in the convergence of quantum software and advanced artificial intelligence represents a critical stabilization point in the deep-tech value chain. As quantum information science transitions from laboratory exploration to industry-specific deployment, research director roles have become structurally necessary to bridge the gap between fundamental algorithmic discovery and scalable product engineering. This position directly mitigates the translation risk inherent in moving long-horizon research through shifting Technology Readiness Levels (TRLs) toward commercial viability. Market signals from global technology indicators highlight that strategic oversight at this specific intersection is essential for safeguarding capital allocations against the swift obsolescence of algorithmic frameworks. By orchestrating the development of hardware-agnostic optimizations alongside neural network compressions, this function establishes the continuous throughput required to deliver deterministic enterprise value. Consequently, the role serves as a primary mechanisms for converting abstract physics and mathematical innovations into repeatable, competitive capabilities within the emerging global quantum economy.
The advanced computing ecosystem is currently shaped by a decisive shift toward hybrid classical-quantum workflows, where the immediate bottleneck lies in the scalability and reproducibility of algorithmic models. Within the software and applications layer of the value chain, organizations are navigating substantial fragmentation across quantum processing modalities and data orchestration standards. This environment demands senior strategic positioning to ensure that multi-disciplinary innovations do not remain localized within isolated academic frameworks but are instead integrated directly into high-performance computing (HPC) and enterprise cloud fabrics.
Current industry focus lies on bridging classical and quantum capabilities at scale while contending with an acute scarcity of deep-tech talent qualified to operate across overlapping scientific domains. Because quantum-inspired solutions provide the most immediate path to enterprise utility, the software layer must balance immediate optimization gains on classical infrastructure with long-term preparedness for fault-tolerant hardware architectures. This operational duality requires organizational structures that can maintain scientific excellence while simultaneously adhering to strict commercial milestones and resource constraints.
Furthermore, macro funding dynamics are increasingly dependent on public-private consortia and national technology strategies, which place a premium on institutional credibility and intellectual property protection. As international regulatory frameworks for trustworthy artificial intelligence mature, deep-tech research organizations must build parallel tracks for rigorous validation and ethical compliance. Managing these complex cross-functional dependencies across distributed scientific teams represents the primary defense against market-entry friction and technological insularity in the global value chain.
The capability architecture for this role type centers on the systemic alignment of mathematical abstraction, tensor networks, and machine learning architectures with enterprise-grade software delivery. Mastery over the interface between variational algorithms and deep learning optimization models is essential for enabling high-throughput model compression and processing efficiency. This structural expertise allows for the parallelization of long-horizon exploratory initiatives alongside near-term development pipelines, minimizing the latency between laboratory validation and deployable technological frameworks.
These domain capabilities matter because they govern an organization’s underlying research throughput and software stability, ensuring that codebases remain resilient across diverse underlying hardware configurations. By instituting precise validation metrics and rigorous peer-review protocols, this architecture provides the necessary analytical leverage to assess the viability of algorithmic frameworks prior to full-scale engineering implementation. Additionally, this cross-functional coupling enables the seamless translation of complex computational kernels into standardized application programming interfaces (APIs), reducing integration friction for external systems and protecting institutional intellectual property. - Accelerates the deterministic transition of hybrid classical-quantum algorithms from theoretical state to production-ready configurations
- Mitigates architectural execution risks by aligning multi-year research trajectories with enterprise technology roadmaps
- Facilitates the standardization of benchmark metrics for evaluating algorithmic performance across disparate hardware modalities
- Optimizes the allocation of specialized scientific resources across concurrent deep learning and quantum software workstreams
- Enhances the translation throughput between fundamental mathematical breakthroughs and deployable enterprise software platforms
- Redduces integration friction within existing high-performance computing infrastructures through standardized co-design protocols
- Safeguards institutional intellectual capital through systematic patent generation and high-impact scientific publication management
- Strengthens cross-functional collaboration frameworks among research scientists, product engineers, and commercial managers
- Minimizes validation cycles for novel model compression techniques utilizing advanced tensor network frameworks
- Leverages academic and public-sector research funding opportunities to amplify internal development capabilities
- Improves the reliability of technology readiness level assessments for executive and investment decision-making portfolios
- Promotes the long-term sustainability of the deep-tech workforce through structured mentorship and leadership pipelinesIndustry Tags: Quantum Computing Software, Artificial Intelligence Optimization, Tensor Networks, Algorithmic Benchmarking, High-Performance Computing Integration, Technology Readiness Translation, Deep Tech Strategy, Deep Learning Architectures, Scientific Leadership
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