The Impact of Technology Readiness Level (TRL) on Compensation

I spent years telling clients that the premium in quantum compensation was for the PhD. Three different investors called me the week Quantinuum announced its latest funding round, and I realised I was only half right. They didn’t ask about qubit modalities or coherence times. They asked, in slightly different ways, the same question: “Where do we find the people who can turn this investment into a product?”

That question changes everything. It signals a fundamental maturation of the quantum industry, away from a purely scientific endeavour and towards an engineering discipline. It is no longer solely about the scarcity of physicists capable of conceiving a novel experiment. It is about the acute scarcity of people who can take a fragile, lab-based curiosity and systematically make it dependable, reliable, and ready for deployment. The capital flooding into the sector, exemplified by Quantinuum securing over $300 million in June 2024 from backers like JPMorgan Chase, Mitsui & Co., and Amgen, isn’t simply a bet on a scientific hypothesis. It is a clear, unambiguous demand for engineering execution and the de-risking of a technical roadmap. Investors are no longer just funding the search for a quantum advantage; they are funding the construction of the advantage itself.

At Quantum People, we have been tracking this profound shift not just in sentiment, but in hard compensation data. Our analysis, which will be detailed in the upcoming QP 2026 Q3 Global Salary Guide, shows a clear and accelerating divergence in compensation packages. The driving variable is no longer just academic specialism or the prestige of one’s publications; it is a candidate’s demonstrated, repeatable experience in moving a technology up the Technology Readiness Level (TRL) scale. The market is now pricing the ability to methodically reduce technical and commercial risk far more highly than the ability to publish a foundational paper. A PhD gets you into the game. Your TRL trajectory wins it.

The compensation signal hiding inside the funding rounds

The capital injection into quantum firms is creating a new compensation tier that prioritises TRL progression over pure academic achievement. The headline funding figures are a useful, if coarse, starting point. According to public announcements, Quantinuum’s latest round brings its total capital raised to around $625 million. PsiQuantum has previously secured over $665 million. These are not academic grants for exploratory research. This is industrial-scale capital, deployed with industrial-scale expectations for tangible, measurable progress towards a commercially viable machine. That progress is increasingly measured using the language of TRLs, a scale adapted for quantum (QTRLs) that runs from basic principles (TRL1) to a proven, operational system (TRL9).

Our data shows that this scale of investment is fundamentally reshaping talent priorities and, consequently, compensation structures. The largest pay packets are no longer reserved exclusively for the architects of novel qubit designs or those at the bleeding edge of theoretical physics. Instead, a significant and growing premium is emerging for individuals who can take a system from TRL4 (component validation in a lab) to TRL6 (system prototype demonstrated in a relevant environment). This specific transition represents the infamous chasm where most deep technology companies falter. It is the brutal, unforgiving leap from a science project that works once, to an engineered system that works repeatedly. The capital markets are now placing enormous bets on the few teams they believe possess the expertise, discipline, and scar tissue to make that crossing successfully.

The impact on salaries is direct and pronounced. While a research scientist focused on fundamental phenomena at TRL2 might command a strong salary reflective of their specialised knowledge, the systems engineer, firmware developer, or quantum software architect tasked with integrating that component into a stable, demonstrable prototype at TRL5 is now often earning more. They are shouldering a different kind of burden: not just scientific discovery, but commercial de-risking and the relentless, unglamorous pursuit of operational stability, uptime, and repeatability. An investor understands that a TRL3 result is a good paper, but a TRL6 system is a defensible asset that unlocks the next, larger funding round and brings a potential product closer to enterprise customers like JPMorgan Chase. They are explicitly willing to fund companies that pay a premium for people who can accelerate that journey through the TRL scale, because each step reduces the perceived risk of their investment.

This trend is creating distinct salary bands that correlate directly with the TRL of the work being performed. Quantum People observes one band for fundamental research and early-stage exploration (TRL1-3), where value is measured in publications and novel concepts. A significantly higher band exists for applied engineering, integration, and subsystem development (TRL4-6), where value is measured in reliability, performance specifications, and system-level demonstrations. Finally, an emerging, top-tier band is forming for productisation, reliability engineering, and system-level optimisation (TRL7+), where value is measured in uptime, manufacturability, and the successful deployment of a system to an end-user. As we detailed in our previous analysis, “The Quantum Compensation Peak,” these peaks in remuneration are increasingly found at the intersection of quantum physics and sound systems engineering, where the complex, messy work of making things actually work, day in and day out, gets done. This shift reflects a market that values demonstrable capability and tangible progression over theoretical potential alone.

What does a ‘high-TRL’ team actually look like?

A high-TRL team resembles a division from a mature technology company, characterised by a diverse skill set that extends far beyond pure physics. A low-TRL team is typically easy to spot; it is often heavy on physicists, many hired directly from academia, with a primary focus on experimental design and the discovery of fundamental phenomena. Their daily work involves tweaking experimental parameters, analysing data from one-off runs, and writing up results for publication. They are built to answer the question, “Can this be done?”

In stark contrast, a high-TRL team is built to answer a completely different set of questions: “Can this be done a thousand times in a row without failure? Can we automate its operation? Can an external user interact with it through a stable API? What is our maintenance schedule?” While physicists remain essential for understanding the core device, they are often outnumbered by systems engineers, software architects, product managers, FPGA developers, and reliability specialists. These are the individuals who build the crucial abstraction layers, the well-engineered control systems, the diagnostic tools, and the application programming interfaces (APIs) that transform a raw quantum device into something a user can effectively program, operate, and derive repeatable results from.

The skills demanded by high-TRL roles are therefore distinct from, and often orthogonal to, those required for early-stage research. A low-TRL role primarily demands creativity in experimental design and a deep, intuitive understanding of quantum phenomena. A high-TRL role, however, demands rigorous discipline in systems integration, meticulous version control for hardware and software, comprehensive documentation, and an unwavering, almost obsessive focus on reliability and uptime. It requires experience in building systems for continuous operation and scalability, not merely for a single, heroic scientific demonstration that works for a few hours under perfect conditions. This fundamental difference explains why Quantum People observes companies with high-TRL ambitions increasingly hiring from outside the traditional quantum bubble. They are systematically recruiting from sectors such as aerospace, semiconductors, high-performance computing, and telecommunications. These industries offer a proven talent pool with decades of experience in building complex, reliable systems that operate at the very limits of physics. They are buying a track record in execution, not just academic credentials.

This strategic talent acquisition has a profound effect on the nature of compensation for high-TRL roles. For a research scientist, the compensation package is often weighted towards a base salary and a bonus tied to research milestones or publications. For a high-TRL systems engineer or product lead, the package structure is notably different. As we explored in “Equity vs. Cash: The True Total Compensation Picture in Deep Tech,” equity becomes a much larger and more significant component of their total remuneration. Their work is directly and visibly tied to hitting the commercial and technical milestones that trigger new funding rounds and directly increase the company’s valuation. Their reward is explicitly linked to the act of making the technology more mature, more stable, and therefore more valuable to investors and potential acquirers. They are being paid to actively reduce technical and commercial risk, and the most effective way to align their incentives with the company’s long-term success is to give them direct ownership of the outcome through a substantial equity stake that vests over several years.

The TRL trap: why the map isn’t the territory

For all its utility as a framework for discussion with investors, the TRL scale has critical shortcomings. It presents a neat, linear progression that rarely reflects the messy, iterative, and often backward-stepping reality of deep technology development. This is a crucial contrarian view that the market is slowly beginning to internalise. A TRL number, while seemingly objective, can often become a vanity metric, used to signal progress to investors without accurately reflecting the true health, stability, or future-proof readiness of the underlying technology.

A company can confidently claim to be at TRL5, for instance, but that single number tells you nothing about the technical debt accumulated to reach that point. It doesn’t indicate whether the system is a bespoke, hand-tuned assembly of lab equipment that only three highly specialised individuals in the world can operate, or if it is a stable, well-documented, and repeatable platform ready for genuine scaling. It doesn’t reveal whether the calibration routine takes ten minutes or ten hours. Crucially, it doesn’t tell you whether the chosen technological path has hit a fundamental scaling bottleneck—a materials science limit, a thermal management problem, a data I/O constraint—that will prevent any further progression without a complete, and costly, re-architecture. The declared TRL can obscure more than it reveals, creating a false sense of security for boards and investors alike.

This is precisely where the most valuable—and, consequently, highest-paid—individuals earn their keep. They possess the experience and critical judgement to look past the declared TRL and assess the actual readiness and scalability of the technology. They can diagnose the hidden complexities, anticipate future integration challenges, and identify the real roadblocks to reaching the next level of maturity. This nuanced skill is rarely taught in PhD programmes; it is primarily learned through the often painful, real-world experience of shipping complex products, managing multi-disciplinary engineering teams through arduous development cycles, and being on-call when a complex system fails at 3 a.m. It is the experience of having seen systems fail, debugging intractable problems, and iteratively improving reliability under intense commercial pressure.

The significant risk for the quantum industry is the emergence of a “TRL bubble,” where capital is allocated based on declared readiness levels that do not stand up to rigorous technical due diligence. We are already observing early signs of this phenomenon. Companies are increasingly hiring for roles with “TRL” explicitly in the title, and candidates are learning to frame their experience in TRL terms to match these descriptions. However, the smart money—and the smartest talent—is focused on the demonstrable substance behind the number. They ask harder, more probing questions that come from the world of mature engineering: How repeatable is the latest demonstration? What is the mean time between failures for the critical components? How large and specialised is the team required to keep the system operational and stable? What does your software regression testing and deployment process look like? The honest answers to these questions reveal far more about true readiness than any single TRL digit ever could.

How to price readiness, not just research

Pricing readiness requires a fundamentally new approach from both employers defining roles and candidates presenting their experience. This shift moves beyond traditional academic metrics like publication record and towards a language of demonstrable engineering outcomes and risk mitigation.

For employers, the job description must evolve. It is no longer sufficient to list requirements for publications in specific journals or years of experience with particular qubit modalities. Instead, a powerful job specification should explicitly define the required TRL jump. For example: “We need a lead engineer to take our photonic interconnects from a lab-validated component (TRL4) to a subsystem prototype demonstrated in a rack-scale environment (TRL6) within 24 months. This will involve defining system requirements, leading a cross-functional team of 5 engineers, and establishing a rigorous testing and validation framework.” This precise language achieves two critical objectives. First, it focuses the talent search on candidates who have delivered tangible engineering outcomes, not just research papers. Second, and equally important, it attracts high-calibre talent from adjacent deep technology industries who may not have direct quantum experience but have successfully made that exact TRL4-to-TRL6 jump with equally complex hardware before. In essence, you are hiring for a proven process of technological maturation and delivery, not solely for domain-specific knowledge.

For candidates, especially those transitioning from academia, this requires a significant reframing of their experience. A CV should be less of a bibliography and more of a portfolio of engineering accomplishments, translated into the language of TRLs. Instead of merely listing a publication, describe the work behind it in terms of the technical leap it represented. For instance: “Led a project that advanced a trapped-ion control system from TRL3 (proof-of-concept) to TRL5 (integrated prototype). This was achieved by developing a new FPGA-based pulse sequencer that reduced timing jitter by 80% and implementing automated calibration routines that enabled 24/7 autonomous operation for the first time.” This reframing directly answers the investor’s question. It demonstrates not just that you can do science, but that you can build, stabilise, and improve a complex technology. It shows you know how to turn capital into a more mature, less risky, and ultimately more valuable asset. That is the skill the market is now paying a premium for.

Sources

• Technology Readiness Level of Quantum Computing Technology …
• Tracking the Development & Assessing the Impact of Quantum …
• The Case for Aligning Ethical Approaches with Technological Maturity
• Quantum Technology Readiness Level (QTRL). – ResearchGate
• Technology Readiness Levels (TRLs) in the Era of Co-Creation – MDPI
• Technology Readiness Levels – NASA
• Technology Readiness Level (TRL) Summaries
• When Will Quantum Technologies Become Part of Everyday Life?
• Technology Readiness Level (TRL) – Overview – AcqNotes
• Adaptation of the technology readiness levels for impact assessment …