At a Glance
- Tasks: Build and enhance AI features for compliance, focusing on document fraud detection and model optimisation.
- Company: Join Arva AI, a startup revolutionising financial crime intelligence with innovative AI solutions.
- Benefits: Enjoy remote work options, competitive salary, equity packages, and bi-annual salary reviews.
- Other info: Opportunity to influence AI strategy in an early-stage startup environment.
- Why this job: Be part of a mission-driven team, shaping the future of compliance with cutting-edge AI technology.
- Qualifications: 3+ years in AI research or engineering, with skills in prompt engineering and model fine-tuning.
The predicted salary is between 36000 - 60000 € per year.
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 80%.
As an AI Research Engineer , you’ll play a pivotal role in building our in-house models—training, fine-tuning, and rigorously evaluating LLMs and agentic systems that power our AI compliance platform, from document fraud detection to web-scale due diligence. You’ll also develop the automation and infrastructure that continuously tests and improves performance (evals, data/label pipelines, training loops, and iterative fine-tuning/distillation).
About the Role
As an AI Researcher, you will:
Build and iterate on in-house LLM and agentic capabilities , integrating them into product features with rigorous evaluation, benchmarking, and backtesting across real compliance workflows.
Design continuous-improvement loops for our models , leveraging human-in-the-loop feedback to drive dataset curation, fine-tuning/distillation, and optimisation of model behaviour.
Stay on the frontier and translate research into impact , exploring and applying new AI methods to improve model quality, explainability, latency, and reliability in production.
What You’ll Do
- Evals: Build benchmarks, evaluate backtests and analyse results to quantify our performance and prevent regressions.
- Model Fine-Tuning: Adapt and fine-tune large language models and vision models for specific use cases.
- Custom Model Training: Train and deploy bespoke AI models tailored to solve unique compliance challenges.
- AI features: Use the latest in LLMs, agents and computer vision to build systems that are faster, more thorough and more accurate than humans.
- MLOps: Ensure that we maintain good practices around collecting and managing datasets, backtests and benchmarks to maximise development velocity.
- Prompt Engineering: Develop and test prompts to optimise model performance and deliver high-quality outputs.
- Collaboration: Work closely with the engineering and product teams to translate customer needs into actionable AI solutions.
- Iterate: Continuously iterate on our AI systems to improve performance, reduce errors, and deliver value to customers.
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: 3+ years in an AI research or engineering role, with experience building and testing agentic systems.
- Technical Expertise: Hands‑on experience with prompt engineering, fine‑tuning pre‑trained models, and training custom models, including vision models. Experience using TypeScript a plus.
- Product Mindset: Strong understanding of how AI can solve real‑world problems, with a focus on customer needs.
- Interests: Ability to stay updated with the latest advancements in AI and apply them effectively.
- Collaboration: Excellent communication skills to work across teams and explain complex AI concepts to non‑technical stakeholders.
- Ownership: A proactive, problem‑solving mindset with the ability to take full responsibility for projects and outcomes.
- Growth‑Oriented: Excited to learn new skills, tackle challenges, and adapt as the company scales.
Why Join Us?
Be part of an early‑stage startup with significant ownership and influence over the AI strategy.
Work on cutting‑edge AI technologies that transform how businesses operate.
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.
Ready to Join the Fight Against Financial Crime?
If you’re excited to shape the future of compliance with state‑of‑the‑art AI solutions, we’d love to hear from you. Apply now to become an Arvanaut as an AI Researcher.
Arva AI is trusted by fast‑growing fintechs like Keep to reduce friction, improve compliance outcomes, and unlock scale
#J-18808-LjbffrAI Research Engineer in London employer: Arva AI Inc.
Arva AI is an exceptional employer located in the heart of Central London, offering a dynamic work culture that prioritises speed, ownership, and transparency. As an AI Research Engineer, you will have the opportunity to work with cutting-edge technologies in a supportive environment that fosters collaboration and innovation, while also benefiting from competitive salaries, equity packages, and flexible working arrangements. Join us to make a meaningful impact in the fight against financial crime and grow your career in a fast-paced startup atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Engineer in London
✨Tip Number 1
Familiarise yourself with the latest advancements in AI, particularly in LLMs and agentic systems. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your hands-on experience with prompt engineering and model fine-tuning by preparing examples of past projects. Be ready to discuss how you approached challenges and what outcomes you achieved.
✨Tip Number 3
Highlight your collaborative skills by preparing anecdotes that demonstrate your ability to work across teams. Being able to explain complex AI concepts to non-technical stakeholders is crucial for this role.
✨Tip Number 4
Emphasise your proactive problem-solving mindset. Think of specific instances where you took ownership of a project or task, showcasing your ability to drive results and adapt as needed.
We think you need these skills to ace AI Research Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in AI research and engineering, particularly focusing on your work with LLMs, prompt engineering, and model fine-tuning. Use specific examples that demonstrate your technical expertise and problem-solving skills.
Craft a Compelling Cover Letter:In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their mission to revolutionise financial crime intelligence and mention any specific projects or achievements that showcase your ability to contribute to their goals.
Showcase Your Technical Skills:Include a section in your application that details your technical skills, especially those mentioned in the job description such as TypeScript, MLOps, and custom model training. This will help the hiring team quickly see your qualifications.
Highlight Collaboration Experience:Since the role involves working closely with engineering and product teams, emphasise any past experiences where you successfully collaborated across teams. Mention how you communicated complex AI concepts to non-technical stakeholders to demonstrate your communication skills.
How to prepare for a job interview at Arva AI Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with prompt engineering, fine-tuning models, and training custom AI models. Bring examples of your previous work that demonstrate your technical expertise, especially in building agentic systems.
✨Understand the Company’s Mission
Familiarise yourself with Arva AI's mission to revolutionise financial crime intelligence. Be ready to explain how your skills and experiences align with their goals, particularly in enhancing operational efficiency and automating compliance tasks.
✨Demonstrate a Growth Mindset
Highlight your eagerness to learn and adapt as the company scales. Share examples of how you've tackled challenges in the past and your approach to staying updated with the latest advancements in AI.
✨Prepare for Collaboration Questions
Since collaboration is key at Arva AI, be ready to discuss how you’ve worked with cross-functional teams in the past. Think of specific instances where you communicated complex AI concepts to non-technical stakeholders effectively.