Job at a glance
KEY RESPONSIBILITIES: Design, build, and optimise machine learning models and pipelines that deliver real business impact Own the full ML lifecycle — from data ingestion and feature engineering through to training, evaluation, deployment, and monitoring Build and maintain MLOps infrastructure to support reliable, repeatable model delivery Collaborate with AI Engineers and data teams to turn business use cases into production-grade ML solutions Build and maintain observability tooling to monitor model performance, drift, and data quality in production Mentor junior engineers in the team — sharing knowledge, reviewing work, and helping them grow Continuously improve model quality, efficiency, and scalability across the product suite QUALIFICATIONS: B.Sc.
degree in Computer Science, Statistics, Applied Mathematics, Data Science, or related field Deep machine learning expertise — strong grasp of algorithms, model selection, and evaluation Solid software engineering skills — you write clean, production-ready code Hands-on MLOps experience — pipelines, experiment tracking, model versioning, and deployment Hands-on cloud experience, AWS preferred Track record of building, deploying, and operating ML systems at scale Experience with observability — monitoring, alerting, and keeping models healthy in production Strong foundations in statistics, mathematics, and data modelling Sharp problem-solving instincts by breaking complex technical challenges into structured, deliverable pieces Clear communicator who can work effectively across engineering and data teams Experience mentoring, supporting, and growing junior engineers Correspondence will only be conducted with short listed candidates.
Should you not hear from us within 14 days then please consider your application as unsuccessful.