Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI and Machine Learning Lead – FinTech SaaS

NLP PEOPLE
City of London
1 month ago
Create job alert
Overview

Miryco Consultants are excited to partner with a rapidly growing, VC-backed SaaS firm specializing in RegTech, aimed at revolutionizing regulatory reporting and compliance for major financial institutions. Their innovative platform automates the reconciliation, validation, and submission of complex derivative transaction data, enhancing accuracy, efficiency, and transparency across capital markets. As the company scales its data and analytics capabilities, they are on the lookout for a visionary and technically adept AI & ML Lead to drive machine learning strategy, model development, and intelligent automation initiatives throughout the platform. This opportunity is perfect for those with a solid ML engineering background, exceptional stakeholder engagement skills, and a strong understanding of financial services data, regulatory logic, or post-trade workflows.


Location: London


Please note, our client is unable to offer sponsorship for this opportunity. If you do not hear from us within five working days after submitting your application, it means you have not been shortlisted for this role. However, we will reach out should other opportunities arise that align with your skills.


For similar roles, please contact Josh Hatton and Tom Parker, and follow Miryco Consultants on LinkedIn.


Responsibilities

  • Take ownership of the firm’s AI/ML strategy, aligning innovative use cases with product objectives and addressing client challenges in the financial services sector.
  • Lead the design and development of ML models for tasks including classification, anomaly detection, NLP, and predictive analytics, utilizing tools such as Python, scikit-learn, PyTorch, or others.
  • Collaborate with data engineering teams to build reliable, secure, and scalable data pipelines that facilitate training, inference, and monitoring of ML models.
  • Drive the operationalization of ML workflows with modern MLOps tools and frameworks, ensuring reproducibility, proper versioning, and monitoring of models in production.
  • Design solutions that accommodate complex structured financial data like trade reporting, EMIR/CFTC records, and regulatory schemas.
  • Work closely with product management and financial services domain experts to translate ambiguous challenges into actionable ML initiatives, partnering with engineering teams to embed models into the platform.
  • Keep abreast of current industry and academic trends in AI/ML, particularly those relevant to RegTech, financial data analysis, or document intelligence.
  • Produce clear documentation and provide training to internal teams regarding the design, function, and behavior of ML systems.

Required Skills & Experience

  • Demonstrated experience designing and deploying machine learning models in production settings.
  • Strong proficiency in Python along with familiarity in ML frameworks such as scikit-learn, PyTorch, or TensorFlow.
  • Experience implementing MLOps practices and tools (e.g., MLflow, SageMaker, Vertex AI, DVC).
  • Knowledge of financial data models, structured datasets, and data validation techniques.
  • Understanding of regulatory reporting, trade lifecycle data, or workflows in capital markets.
  • Experience with cloud platforms like AWS, GCP, or Azure and scalable data solutions.
  • Exceptional communication skills with the ability to convey findings to both technical and non-technical stakeholders.

Nice to Have

  • Experience in RegTech, capital markets, or post-trade analytics.
  • Familiarity with Snowflake, dbt, or related cloud data warehousing technologies.
  • Background in anomaly detection, rule-based AI, NLP, or data reconciliation.
  • Hands-on knowledge of version-controlled notebooks, CI/CD for ML, or containerization (Docker/Kubernetes).

Core Competencies

  • Strong problem-solver with a data-driven approach.
  • Practical and commercially aware in applying AI/ML solutions to financial services use cases.
  • Independent thinker who thrives in dynamic and uncertain environments.
  • Collaborative team player, eager to exchange knowledge and insights.
  • Dedicated to ethical AI practices, data integrity, and model explainability.

Company: Miryco Consultants Ltd


Educational level: Senior (5+ years of experience)


Language requirements:


Level of experience (years): Senior (5+ years of experience)



#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Scientist

Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Data Scientist - New Applications

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.