Senior Machine Learning Engineer

About Intent HQ

Recognised by the Financial Times as one of the FT1000 Fast growing companies in Europe in 2022 and 2023, Intent HQ is a leader and innovator in Customer AI Analytics and Data Science with a blue chip international enterprise customer base and solid financial backing from our investors. Our mission is to become the world’s preeminent Customer Intent platform by bringing together privacy-first signals intelligence, proprietary behavioural AI/ML analytics & uniquely accessible enterprise insights into a single platform that organisations will use to build more genuine, sustainable and profitable relationships with their customers. . Our initial focus solved problems for clients in the telecommunications sector, including Verizon & Orange. We have since expanded into the Financial Services, Retail and Social Media sectors including HB Reavis and Zurich Group as clients to name a few.

Our clients typically have tens of millions of customers and billions of interaction events each day. We have developed our platform to handle data at this enormous scale efficiently. Intent HQ is unique because we've focused on understanding customer interaction data. We do the hard-specialised work leaving our clients free to focus on integrating the insight into their business, with one Client seeing an additional £26m annual revenue as a result of using our products and services.

Intent HQ is an exciting place to work, we are very proud to have made our debut on the FT1000 Fastest Growing Companies in Europe for 2022! We have a talented team of circa 100 -people (and growing!) based in & around London, Barcelona, Lisbon and New York & Tel Aviv, collectively speaking over 15 languages!

Why Join Us:

• Exciting Work Environment: Work on cutting-edge technology at the intersection of AI and data analytics.

• We are Winners: AI Company of the year 2024 & Best in Tech Employer Women in Tech awards 2022 & 2023

• Growth Opportunities: Advance your career in a fast-paced, innovative industry.

•  Hybrid & flexible working

The Opportunity:

 Are you an expert at engineering and operating large-scale data and machine learning systems with high reliability and efficiency? Do you thrive in environments that are data-driven and innovation-focused?

We are looking for a Senior Machine Learning Engineer who is passionate about leveraging data, scaling ML systems, and building robust MLOps pipelines to deliver AI solutions at scale. You will collaborate with data scientists, product teams, and engineers to design and maintain the infrastructure that powers our AI products, with privacy, security, and data ethics as core principles.

At Intent HQ, we work on understanding customer behaviors by processing over 100 billion events daily, providing deep insights into what millions of customers do, how they think, and who they are. Our work fuels high-impact products, and we are looking for someone who can help us scale these efforts even further.

Key Responsibilities:

• Design, implement, and manage our end-to-end Data & ML Platform, which supports all AI product development and deployment. This includes developing and improving data pipelines, feature engineering for downstream models, and orchestration of complex data workflows.
• Productionise machine learning models and manage them across the full lifecycle—from model training to deployment and monitoring—while ensuring scalability, security, and performance.
• Advise on architectural patterns and tooling to enable data and machine learning workloads at scale. You’ll work closely with data scientists to ensure the platform supports experimentation, model training, and inference efficiently.
• Collaborate with product and consulting teams to design and deliver platform capabilities that directly benefit our customers.
• Champion a culture of experimentation and continuous improvement by taking ownership, learning from mistakes, and contributing to the growth of your colleagues.

What we’re looking for:

Required

• 7+ years of industry experience writing clean, production-grade code, with a deep focus on data engineering, machine learning and MLOps workflows.
• Expertise in distributed data processing frameworks such as Spark, handling multi-terabyte datasets to generate valuable insights.
• Proficiency in building and orchestrating data and machine learning pipelines, supporting data engineering, model training,