Tuning

Location: Basingstoke, Hampshire. This is an in-office role, and as such, will require you to live within a reasonable commute. Contract: Casual hourly contract Working Hours: Shifts typically 10 - 12 hours Hourly Rate: £13.00 - £18.20 Per Hour (exact rate will vary depending on role) Start Date: July/August 2026 WHY HAWK-EYE & WHY THIS ROLE?: We are looking for candidates to play a key part in delivering Goal Line Technology (GLT) at our centre in Basingstoke; however, there is scope for successful candidates to be offered further opportunities in delivering Electronic Performance and Tracking Systems (EPTS) and Semi-Automatic Offside (SAO) in elite football competitions. Having successfully deployed this system across UEFA competitions, we are now expanding our remote operations to include the Premier League and Championship. Based in the Remote Operations Centre (ROC) at Hawk-Eye’s Head Office in Basingstoke, you'll play a crucial role in operating cutting-edge technology, liaising with Hawk-Eye colleagues on the ground across the UK, and a range of external stakeholders, contributing to the excitement of live sports events. While this is a casual contract, we are seeking candidates with full availability across the week. This role is designed for those looking to commit to significant hours, particularly during peak periods of the football calendar. WHAT DOES A TYPICAL DAY LOOK LIKE? For a typical 3pm kick off you can expect our call time to be 5 to 6 hours prior to the start of the match. Throughout the day you will be faced with several hard deadlines in which you will have to meet in order for the service to run effectively and efficiently. Initially, you will spend the first part of your day testing communications, calibrating, and optimising the technology. This ensures GLT is fully operational two hours prior to kick-off, allowing match officials to test its integrity. Warm up is our final opportunity to ensure the system is fully functional before we enter the live match. During the live match you will be monitoring the data, fine tuning the calibration and constantly preparing to produce a virtual replay for broadcasters should a goal line incident occur and activate our GLT system. To summarise, these would be the key components of the role: * Operation of the GLT system from the ROC during matches; * Match Day calibration of the GLT system * Monitoring of GLT live data * Delivering graphics and virtual replays for GLT and which will be shared with the TV audience worldwide * Collaborating with supervisors and on-site staff to ensure the system is operated to the highest standard * Investigating/troubleshooting software issues as technical support for the on-site team ESSENTIAL SKILLS, ATTRIBUTES, AND REQUIREMENTS: * A technical grounding * Strong problem-solving skills * A willingness to learn * Excellent communication skills, punctuality and ability to follow instructions and work towards a shared goal * Ability to work flexibly, including weekday evenings and weekends for matches in line with match schedules * Live within a commutable distance of the Remote Operating Centre, Basingstoke (RG22) Desirable Attributes: * Experience, background or qualification in a technical-related course such as computing, computer science, engineering, mathematics, science or technology. * Understanding of PC networks and data collection * Camera optimisation At Hawk-Eye Innovations, we appreciate and value the importance of potential and growth. If you believe that you excel in certain areas and possess the passion and desire to develop further, we encourage you to apply. AVAILABILITY AND TRAINING: Please Note: While this is a casual contract, matches take place strictly according to the football calendar. The journey will begin with training and testing during global sporting events from July and into August. It is crucial that you are able to provide a good level of availability to regularly contribute and participate in these exposure and training opportunities over the initial training period. The ultimate goal is that by the opening weekend of the Premier League in August we will have a pool of operators who are ready to deliver GLT across multiple competitions. This role will have an initial focus on UEFA Football events while you train and gain experience in operating our system, with successful candidates then being given further exposure during our EPL and EFL operations. A typical shift would start 6 hours before the designated kick-off time to set up and test technology. The end of the shift is dependent on service, but typically would be 1 or 2 hours after the match has finished. WHAT DIFFICULTIES MIGHT I FACE? Up to this point, while there may be many things that you find intriguing about this role, the difficulties you may face should not be ignored. * Working Hours: Due to the nature of the sports industry, there is often work on weekends and midweek evenings, and we are expected to fulfil our roles until the final whistle and takedown is complete. * High-Pressure Situations: Working in a live broadcast environment on a production that is distributed to millions worldwide will bring high levels of pressure. We will do our best to train and equip you to the best possible level to help with these, however it is important to consider how you naturally navigate high-pressure environments, and whether this fast-paced role is the right fit for you. TEAM CULTURE At Hawk-Eye, we pride ourselves on a collaborative, high-performance culture where trust, passion, and innovation thrive. We believe in fostering an environment where every team member is empowered to push boundaries and contribute to the future of sports technology. Our work is guided by three core values: * We are Brave: We challenge the status quo, embrace big ideas, and constantly seek new ways to innovate in the sports entertainment industry. We aren't afraid to take risks in pursuit of excellence. * We are Owners: We take personal accountability for our work, our decisions, and our collective success. We celebrate our wins together and treat every challenge as an opportunity to learn, grow, and improve. * We are Inclusive: We believe our diversity makes us stronger. We cultivate a welcoming environment where unique perspectives are valued, all while being united by our shared love for sports and technology.

SUMMARY OF THE ROLE: Maze is building an AI-native vulnerability management platform. Our autonomous agents investigate, triage, and remediate security findings the way a senior analyst would, only faster and at scale. As Head of AI, you'll own the intelligence that makes those agents work: the AI research and implementation strategy for the whole company, plus the crown-jewel technical problem underneath it. Our investigation agents run multi-step, non-deterministic trajectories across a toolset of 180+ tools, tested against a ground-truth exploit lab we built for exactly this purpose. Knowing whether they're getting better, and making them better, is the most important technical problem at Maze. It's the heart of this role. This is a hands-on leadership role, not a management layer. You'll set AI direction as a member of the engineering leadership team reporting to the CTO. But you'll spend most of your time building: designing evaluation frameworks for non-deterministic agents, running fine-tuning and model-routing experiments against real data, prototyping new techniques and getting them into the product. You'll lead a small, strong AI team (3–4 engineers today) by setting the technical bar and doing the work alongside them, while working closely with our ML tech lead and the product teams building agents day to day. Your impact comes from what you ship, not the size of your org. We're not looking for someone to run a large team from two layers up. We're looking for someone who wants to define how generative AI transforms cybersecurity and keep their hands on the code. This role suits a deep LLM-era practitioner who has shipped agentic systems to production, can reason about transformer internals and fine-tuning from first principles, and moves fast. We're a three-product company with a lot of surface area, a well-funded Series A (Theory Ventures) behind us, and a Series B on the horizon. The AI foundation you set now becomes the moat we compete on for years — this is a foundational hire whose standards will shape Maze's AI trajectory well past this raise. YOUR CONTRIBUTIONS TO OUR JOURNEY: * Own AI strategy and research direction: Set the technical roadmap for our AI capabilities. Stay ahead of the research curve to find, validate, and prioritise the techniques that differentiate Maze, and turn what's real into a concrete, sequenced roadmap while discarding the hype. * Own agent quality and evaluation: Build and run the frameworks that tell us whether our investigation agents are improving. That means trajectory evaluation, ground-truth scoring against the exploit lab, and end-to-end benchmarks for non-deterministic, multi-step behaviour. This is the core problem of the role. * Build the breakthroughs yourself: Prototype a new technique in days, get it into the product, and measure the impact. You'll spend most of your time hands-on in the codebase, acting as the technical product manager who guides it to production. * Run fine-tuning and model experiments on real data: Own fine-tuning pipelines, context engineering, model migration, and cost/routing optimisation grounded in production data, not proofs of concept. * Guide prioritisation across the AI team: New techniques, papers, and ideas surface constantly. You'll be the filter deciding which of them are actually worth a prototype this week, and which are noise - keeping the team focused on what moves the needle. * Lead a small team by doing: Set technical direction for the AI engineers, raise the bar through pairing and review, hire as we scale, and stay close enough to the work to make the hard architectural calls yourself. * Partner with the CTO and engineering leadership: Turn the AI roadmap into shipped capability, and make sure evaluation is wired into how the whole team builds. * Get in front of customers: Occasional direct customer exposure, translating what security teams need into concrete improvements to the ML pipeline. * Set the pace: Ship prototypes in days, not quarters. Bring urgency to a domain where most of the field still moves slowly. WHAT YOU NEED TO BE SUCCESSFUL: * Hands-on technical leadership: A track record of leading AI work while personally building it. Strategy and implementation. You lead from the front. If you've moved permanently into management and stopped shipping, this isn't the right fit. * Shipped LLM/agentic systems to production: You've built and run generative-AI systems that real customers use, not research prototypes or slideware. You can point to agents or LLM features you put into production and improved over time. * Deep LLM-era technical depth: You can explain transformer architecture, training, fine-tuning (e.g. LoRA), and inference from first principles. We test this directly. A strong pre-LLM ML pedigree (RL, NLP, recommendations, ASR) is valuable but won't substitute for modern generative-AI depth. * Built evaluation frameworks for non-deterministic systems: You've designed and run evals for multi-step, non-deterministic agents: trajectory evaluation, LLM-as-judge, fine-tuning result measurement. This capability is rare and it's the one we most want. It will set you apart. * Top-tier pedigree with a builder's edge: Experience at a leading AI organisation or strong AI-native startup where you raised the technical bar rather than coasted on the brand. * Unambiguous startup signal: You've operated at early stage or built something from zero. You move fast, own outcomes end-to-end, and don't need a large org around you to ship. Founder experience is a strong plus. * Pace and urgency: You ship prototypes in days. You make pragmatic calls on models, cost, and scope to keep momentum, and you're impatient with quarters-long cycles. * Sharp, concise communication: You communicate clearly and tightly in a remote-first, English-speaking team, in writing and live. You get to the point. * Nice to Haves: * Security, vulnerability-management, or adversarial-domain background. Strongly preferred. Every candidate we've rated highly has had it. Offensive security, vuln management, threat detection, or applying AI to security problems all count. * Comfort in front of customers, able to translate agent behaviour and capability into terms a security team understands. * Model cost/routing pragmatism: real experience cutting inference cost and migrating between models in production. * Track record at a successful AI-first startup, scaling a system from experimentation to production impact. * PhD or published work in ML/AI at top-tier venues, paired with real production experience. YOUR FIRST 90 DAYS * Days 1–30: Get fully up to speed on every agent we've built and how our ML evaluation pipeline works today. Start drafting a short, mid, and long-term technical plan. * Days 31–60: Ship something fundamentally new — for example, fine-tune a small model and get it into production. * Days 61–90: Move onto bigger bets — RLHF for specific use cases, scalability of the evaluation approach, and deeper customer-facing model tuning.   THIS ROLE IS NOT FOR: * Manager-of-managers or 2nd/3rd-line leaders who direct rather than build. * Fractional, advisory, or part-time profiles. * Research-only backgrounds without production shipping experience. WHY JOIN US: * The hardest problem in the field, unsolved. Evaluating non-deterministic, multi-step agents against ground truth is an open problem, and we've built the exploit lab and 180+ tool agent infrastructure to attack it. You'd own it, at the intersection of generative AI (LLMs and agents) and cybersecurity. * A team you'll want to be measured against. Founders and engineers from Amazon, Elastic, and Tessian. Hands-on leaders who've been part of multiple acquisitions and an IPO. Most people who join do so because of how strong the team already is. * Build the AI-native company from the ground up. A well-funded Series A (Theory Ventures) with a Series B on the horizon, early enough that you'll set the technical standards for how AI investigates security at scale. * Cybersecurity as a force for good. The work directly helps organisations stop attacks. Measurable impact, real customers, immediate feedback on what you ship. * Founding-level ownership and upside. Significant equity, a seat on engineering leadership, and a path to VP of AI as the team scales around what you build.