Principal Machine Learning Engineer in London

Principal Machine Learning Engineer in London

London Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
Complyadvantage

At a Glance

  • Tasks: Lead the engineering build-out of ML and AI systems to combat financial crime.
  • Company: Join ComplyAdvantage, a leader in financial crime risk intelligence.
  • Benefits: Enjoy equity participation, unlimited time off, and a hybrid work model.
  • Other info: Collaborate with smart professionals and enjoy career development opportunities.
  • Why this job: Make a real impact in fighting financial crime with cutting-edge technology.
  • Qualifications: Extensive experience in ML, Python, and architectural design of MLOps platforms.

The predicted salary is between 80000 - 100000 £ per year.

We are looking for an exceptional Principal Machine Learning Engineer to lead the engineering build-out of ML and agentic AI across our AML/KYC and Fraud platform. Our products use ML, LLMs and agentic systems to extract entities, risks and relationships from millions of structured and unstructured sources, to score customer, transaction and fraud risk, and to power our real-time financial crime knowledge graph.

As a Principal MLE you will be a senior technical leader who builds the systems that bring our ML and agentic AI work to production. You will report into the VP of Engineering, working in alignment with the strategic direction set by the Director of Data Science, who owns AI/ML and data governance direction at ComplyAdvantage. Your remit is execution: the architectural design of our company-wide MLOps and agentic AI platforms, the build-out of new models and agent systems, and the engineering bar across all of it. You will also represent ComplyAdvantage at conferences and industry forums. Your impact will shape how ComplyAdvantage uses ML across the company, and through that, how our customers detect money laundering, terrorist financing, sanctions evasion and other financial crime.

Your work will help evolve a financial crime knowledge graph that spans public and private data, and is helping our customers make financial crime a thing of the past.

Scope & Key Responsibilities

  • Architectural Leadership: Lead the architectural design and implementation of our company-wide MLOps and agentic AI platforms, covering training, evaluation, serving, feature/vector stores, and agent orchestration.
  • Strategic Execution: Translate the ML and agentic AI roadmaps set by the Director of Data Science into scalable engineering deliverables, ensuring all production builds closely adhere to established data governance frameworks and compliance standards.
  • Engineering Rigor: Set the engineering bar across the organization for code quality, rigorous evaluation design, operational standards, and CI/CD pipelines.
  • Advanced AI Implementation: Lead the end-to-end engineering build-out of AI systems pioneered and prototyped by Data Science, including LLMs, retrieval augmented generation (RAG), multi-agent systems, and graph neural networks.

Our Tech Stack:

  • Our technology stack is designed to run on public cloud architectures, notably AWS and GCP.
  • Development is organised around Kotlin and Python for our backend languages and TypeScript/ES6+React for our frontend stack.
  • We make substantial use of relational database technologies, notably Postgres, Yugabyte.
  • We also use an event-sourced model powered by Kafka for our communication bus and gRPC for our intra-service communication protocol.
  • We use modern observability solutions from Grafana Cloud and deploy our code using ArgoCD.
  • We have a strong emphasis on engineering excellence and strive to ship the best possible code and the best possible solutions to our customers.

About you

As a Principal Machine Learning Engineer with company-wide impact, you will bring:

  • Substantial experience building, training and productionising machine learning models at scale, including modern deep learning and large language model approaches.
  • Deep production Python experience, strong software engineering fundamentals (design patterns, event-driven architectures, observability), and an instinct for what makes a model and a system maintainable in the long run.
  • Strong mathematical and statistical foundations. You can act as the company's go-to expert on rigorous, defensible application of techniques.
  • Experience leading the architectural design of MLOps platforms: training pipelines, feature and vector stores, serving infrastructure, and drift and performance monitoring.
  • Experience with cloud (GCP and AWS), containerised infrastructure (Kubernetes, Docker, ArgoCD, Argo Workflows), event brokers (Kafka) and modern data engineering workflows (batch, streaming, ETL).
  • Experience turning a directing scientist's or product owner's brief into ML work that ships and delivers measurable value, and pushing back where feasibility, data quality or risk make stated goals unrealistic.
  • Excellent written and verbal communication. You can engage senior stakeholders and engineers, and produce technical documentation people can act on.
  • A track record of coaching ML engineers at every level and of helping Recruiting improve the hiring process.

Nice to have

  • Experience applying ML, LLMs and agentic AI in AML, KYC, fraud, TegTech or another regulated domain.
  • Familiarity with knowledge graphs, entity resolution, link analysis and temporal reasoning over relationship data.
  • Experience designing evaluation frameworks for LLM and agentic systems, including safety, accuracy and operational guardrails.
  • External profile in the ML community: speaking at conferences, contributing to publications or open-source projects.

Benefits:

  • Equity participation in our innovative mission to combat financial crime.
  • Unlimited Time Off Policy to promote work-life balance and well-being.
  • We embrace a hybrid approach that requires employees to be in the office for two days a week.
  • Opportunities for collaboration and career development with smart, like-minded professionals.
  • Annual learning budget to support professional growth.
  • A home office budget to support working from home.
  • Enhanced parental leave and childcare benefits.
  • Life insurance and medical coverage through BUPA, including pre-existing conditions.
  • Pension contribution through The People's Pension.

About us:

Our mission is to empower every business to eliminate financial crime. By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust. More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence.

With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff. ComplyAdvantage is headquartered in London and has global hubs in New York, Lisbon, Singapore, and Cluj-Napoca. It is backed by Balderton Capital, Index Ventures, Ontario Teachers’ Pension Plan, Goldman Sachs, and Andreessen Horowitz.

Learn more about compliance re-engineered for the age of AI at complyadvantage.com.

Principal Machine Learning Engineer in London employer: Complyadvantage

ComplyAdvantage is an exceptional employer that champions innovation and collaboration, offering a dynamic work environment in London where you can lead the charge in machine learning and AI to combat financial crime. With benefits like unlimited time off, equity participation, and a strong emphasis on professional growth through annual learning budgets, employees are empowered to thrive both personally and professionally. The hybrid work model fosters meaningful relationships while allowing for flexibility, making it an ideal place for talented individuals looking to make a significant impact in the field of financial technology.

Complyadvantage

Contact Details:

Complyadvantage Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Principal Machine Learning Engineer in London

Tip Number 1

Network like a pro! Get out there and connect with folks in the industry. Attend meetups, conferences, or even online webinars related to machine learning and AI. You never know who might be looking for someone just like you!

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving ML and agentic AI. Share your work on platforms like GitHub or even your own website. This gives potential employers a taste of what you can do.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.

Tip Number 4

Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at ComplyAdvantage. Tailor your application to highlight how your experience aligns with our mission to combat financial crime.

We think you need these skills to ace Principal Machine Learning Engineer in London

Machine Learning
Large Language Models (LLMs)
Agentic AI
MLOps
Architectural Design
Python
Kotlin

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Principal Machine Learning Engineer role. Highlight your experience with ML, LLMs, and agentic AI, and don’t forget to mention any relevant projects or achievements!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about combating financial crime and how your background makes you the perfect fit for our team. Keep it engaging and personal!

Showcase Your Technical Skills:We want to see your technical prowess! Include specific examples of your work with Python, MLOps platforms, and cloud technologies. If you've led architectural designs or built production systems, make sure to highlight those experiences.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our mission at ComplyAdvantage!

How to prepare for a job interview at Complyadvantage

Know Your Tech Stack

Familiarise yourself with the technologies mentioned in the job description, like Python, Kotlin, and cloud platforms such as AWS and GCP. Be ready to discuss how you've used these tools in your previous projects, especially in building and deploying ML models.

Showcase Your Architectural Skills

Prepare to talk about your experience in designing MLOps platforms and how you ensure compliance with data governance frameworks. Bring examples of past projects where you led architectural decisions and how they impacted the overall system performance.

Demonstrate Your Leadership

As a Principal Machine Learning Engineer, you'll need to show that you can lead teams and mentor others. Think of specific instances where you've coached engineers or improved hiring processes, and be ready to share those stories.

Communicate Clearly

Strong communication skills are key for this role. Practice explaining complex technical concepts in simple terms, as you'll need to engage with both technical and non-technical stakeholders. Prepare to discuss how you create actionable technical documentation.