Senior Machine Learning Engineer (Customer/Marketing)

Location: London, England, United Kingdom; hybrid workplace

Company

hirify.global combines fashion and technology to operate a platform used by millions of customers.

What you will do

• Design, build, deploy, operate, monitor, and optimise machine learning systems for customer engagement, marketing effectiveness, pricing, personalisation, and commercial decision-making.
• Own the end-to-end engineering lifecycle, including data ingestion, feature engineering, productionisation, and operational reliability.
• Partner with Applied Scientists, Data Engineers, and Machine Learning Engineers to turn research and experimentation into scalable production systems.
• Build reusable tooling, frameworks, feature platforms, and infrastructure that accelerate machine learning delivery and reduce operational overhead.
• Contribute to MLOps platform capabilities, engineering best practices, observability, CI/CD, and operational excellence.
• Influence technical direction and architecture, mentor colleagues, and uphold engineering quality, reliability, and scalability.

Requirements

• Experience building, deploying, and operating machine learning systems in production environments.
• Strong software engineering fundamentals, including expertise in Python and modern engineering practices.
• Experience building scalable batch and real-time machine learning pipelines in cloud environments.
• Strong understanding of MLOps, including model deployment, monitoring, CI/CD, observability, and operational excellence.
• Experience with large-scale data processing technologies such as Spark and machine learning frameworks such as PyTorch, TensorFlow, XGBoost, or similar.
• Experience designing reliable APIs, services, platforms, feature platforms, ML platforms, or shared machine learning infrastructure.
• Ability to work through ambiguity and lead complex technical initiatives.
• Experience in customer intelligence, marketing optimisation, pricing, forecasting, or personalisation, plus exposure to experimentation frameworks, causal inference, or measurement platforms.
• Experience mentoring engineers, influencing technical direction beyond the immediate team, and delivering machine learning solutions with measurable customer or commercial outcomes.

Culture & Benefits

• Full-time employment in a hybrid workplace.
• Employee discount and access to employee sample sales.
• 25 days of paid annual leave plus an additional celebration day.
• Discretionary bonus scheme and private medical care scheme.
• Flexible benefits allowance that can be taken as cash or used for other benefits.
• Personalised learning and in-the-moment development experiences.