Head of Research

Arva AI; Greater London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Bi-annual salary review

Equity package

Remote work flexibility - 4 weeks/year

Job summary

Arva AI is seeking a Head of Research to lead the in-house AI research, agentic systems, and evaluation infrastructure powering AML solutions. You’ll set the research agenda, build and mentor a team, and stay hands-on with training, fine-tuning and rigorous evaluation to outperform human reviewers in live regulatory workflows.

You will own research strategy, roadmaps, and the productionization of models, ensuring high explainability, latency and reliability while collaborating with product,

Qualifications

• 5+ years in applied AI research or ML engineering with leadership experience
• Experience training and evaluating LLMs and vision models
• Ability to translate research into production for AML/compliance use cases

Responsibilities

• Own Arva's AI research strategy and roadmap, deciding in-house vs frontier-model work
• Build and lead the research team, set rigorous practices to production
• Own model quality, evaluation stacks, and documentation for regulators
• Train, fine-tune and deploy LLMs and vision models for compliance use cases
• Maintain MLOps practices for reproducibility and velocity
• Partner with product/engineering to ship research-driven solutions and articulate edge to customers

Skills

AI research leadership

LLM fine-tuning

Production ML

Team management

Regulatory/compliance awareness

Education

PhD in ML or related field (nice to have)

Tools

MLOps

Job description

Location: In person, Central London, 4-5 days in office

Type: Full-Time

NB: We are able to sponsor visas

Arva AI is revolutionising financial crime intelligence with our cutting-edge AI Agents. By automating manual human review tasks, we enhance operational efficiency and help financial institutions handle AML reviews, while cutting operational costs by 85%.

As Head of Research, you will lead the research function behind our AI Agent platform: the in-house models, agentic systems and evaluation infrastructure that power everything from document fraud detection to web-scale due diligence. At Arva, model quality is the product. You'll set the research agenda, build and lead the team that delivers it, and stay hands-on: training, fine-tuning and rigorously evaluating systems that must be faster, more thorough and more accurate than human reviewers in live, regulated workflows.

About the Role

As Head of Research, you will:

• Own Arva's AI research strategy, deciding where we build in-house capability, where we adapt frontier models, and which bets compound into a durable technical edge.
• Build and lead the research team, setting the technical bar and the practices that get research into production quickly and safely.
• Own model quality as a company-level outcome, from evaluation methodology and benchmarks through to the accuracy, explainability, latency and reliability of what runs in front of customers and regulators.

What You'll Do

Research Strategy & Roadmap

• Define and own the research roadmap, grounded in customer workflows, regulatory realities and the frontier of what LLMs, agents and vision models can do.
• Make clear build-vs-adapt decisions: when to fine-tune or distil, when to train bespoke models, and when to lean on frontier APIs.
• Translate new research into production impact, continuously assessing emerging methods for their effect on quality, explainability, latency, cost and reliability.

Team Leadership

• Hire, develop and retain exceptional AI researchers and engineers, and set the standard for rigour and ownership across the team.
• Run the team's operating cadence: planning, prioritisation, reviews and clear accountable ownership for every initiative.
• Lead from the front on the hardest problems, from training runs and eval design to failure analysis.

Evaluation & Model Quality

• Own the evaluation stack: benchmarks, backtests and regression suites that quantify performance against real compliance workflows and catch regressions before customers do.
• Build continuous-improvement loops that turn human-in-the-loop feedback into dataset curation, fine-tuning and distillation, and measurable gains in model behaviour.
• Establish the model documentation and validation practices that regulated financial institutions, and their auditors, expect of the AI they rely on.

Models & Infrastructure

• Train, fine-tune and deploy LLMs and vision models for specific compliance use cases, from document fraud detection to entity screening and web-scale due diligence.
• Maintain MLOps practices around datasets, labels, backtests and benchmarks that maximise development velocity without sacrificing reproducibility.

Cross-Functional Leadership

• Partner with product and engineering to shape feasible, scalable solutions and get research into customers' hands fast.
• Support GTM in articulating our technical edge in customer conversations, technical due diligence and launches.
• Represent Arva's research externally where it serves the mission, through publications, talks and the wider AI and compliance community.

Our Culture

Deliver Value Fast

Speed starts with clarity. We first understand what value actually means, for the customer, the business, or the system, and then take the shortest credible path to delivering it. We move quickly without cutting corners on quality, security, or trust.

Outcome Obsessed

We obsess over details and take full ownership of wider outcomes, not just tasks. We think like the user, execute with rigor, and validate that every detail works in real conditions. If something falls short, we fix it properly and prevent recurrence, always raising the bar.

Relentless Urgency

We move with urgency because time matters. We prioritise what truly moves the outcome, make decisions with imperfect information, and act decisively. Urgency means focus, momentum, and driving meaningful progress without unnecessary delay.

What We're Looking For

Experience

• 5+ years in applied AI research or ML engineering, with a track record of leading teams and owning a research agenda through to production.
• A PhD in machine learning, AI or a related field is a nice to have, not a requirement.

Technical Depth

• Hands-on expertise training and fine-tuning LLMs and vision models, building and testing agentic systems, and designing evaluations that hold up in production.
• Experience with distillation, RL-based post-training or inference optimisation is a strong plus. Experience using TypeScript a plus.

Research Judgment

• Ability to separate what is truly promising from what is merely new, and to sequence research bets against near-term customer impact.

Product & Customer Focus

• Strong understanding of how AI solves real-world problems, and the ability to connect model behaviour to customer outcomes in AML, compliance and risk. Domain experience in regulated industries is a plus, not a requirement.

Communication & Collaboration

• Clear, concise communicator who can explain complex AI concepts to executives, customers and non-technical stakeholders, and align researchers, engineers and commercial teams around a shared plan.

Ownership

• Comfortable taking full responsibility for outcomes, decisions and results, and for building the team that delivers them.

Why Join Us?

• Be part of an early-stage startup, building and leading its research function from the ground up with significant ownership and influence over AI strategy.
• Work at the frontier of applied AI on problems where accuracy, explainability and trust are non-negotiable.
• Collaborate with a passionate, mission-driven team dedicated to innovation.
• Work from anywhere in the world for 4 weeks a year, in addition to regular team off-sites.
• Competitive salary and equity package, with bi-annual salary review and yearly performance-based equity refresh.