Machine Learning Engineer
Core
Design and deploy next-generation AI and machine learning solutions at scale, focusing on production-ready models and robust ML pipelines.
Role type
Machine Learning Engineer
Builds
Production ML models, scalable ML pipelines, and modern AI capabilities
Domain
Artificial Intelligence / Machine Learning
Deliverable
production ML models
Required skills
Machine learning engineering, software engineering, PyTorch, scikit-learn, LangChain, end-to-end ML lifecycle, CI/CD, data processing, large-scale data systems, API deployment, container orchestration, cloud platforms
Preferred skills
Computer vision, natural language processing, generative AI, agent-based systems
Technologies
PyTorch, scikit-learn, LangChain, AWS, Azure, GCP
Responsibilities
Design, develop, and deploy machine learning models and AI systems into production; Build and maintain scalable ML pipelines covering data ingestion, training, evaluation, deployment, and monitoring; Collaborate with cross-functional teams to translate business requirements into AI/ML solutions; Optimise models and systems for performance, scalability, and reliability; Implement MLOps best practices including CI/CD, model versioning, experiment tracking, and automated retraining; Monitor and maintain model performance, including handling drift and system reliability; Develop and integrate AI capabilities across domains such as computer vision, natural language processing, and generative AI; Ensure adherence to data governance, security, and best engineering practices
Seniority
Mid-level, hands-on IC