Machine Learning Engineer
5 days ago
Leeds
Position Overview • We are seeking a highly skilled Machine Learning Engineer to design, build, deploy, and optimise machine learning models that power data-driven products and business solutions., • This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance., • The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working in a fully remote, collaborative environment within the UK. Key Responsibilities 1. Machine Learning Model Development • Design, develop, train, and evaluate machine learning models for prediction, classification, recommendation, or automation use cases., • Apply supervised, unsupervised, and deep learning techniques as appropriate., • Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment • Deploy ML models into production using scalable, reliable architectures., • Build and maintain APIs or batch pipelines for model inference., • Monitor model performance, data drift, and retraining needs. 3. Data Engineering & Pipelines • Collaborate with data engineers to design efficient data ingestion and transformation pipelines., • Work with structured and unstructured data from databases, APIs, and data lakes., • Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation • Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking., • Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML., • Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure • Build ML solutions on cloud platforms such as AWS, Azure, or GCP., • Use containerization and orchestration tools (Docker, Kubernetes)., • Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement • Work closely with Data Scientists, Product Managers, Software Engineers, and Analysts., • Translate business requirements into scalable ML solutions., • Communicate model behaviour, limitations, and results clearly to non-technical stakeholders. 7. Research & Continuous Improvement • Stay current with advancements in machine learning, AI, and data science., • Evaluate new algorithms, tools, and frameworks for potential adoption., • Contribute to best practices, documentation, and knowledge sharing. Required Skills & Experience Core Technical Skills • 3+ years of experience in Machine Learning, Data Science, or related roles., • Strong programming skills in Python., • Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost., • Solid understanding of ML algorithms, statistics, and evaluation metrics., • Strong SQL skills and experience working with large datasets., • Familiarity with data processing tools (Pandas, NumPy, Spark)., • Experience building APIs (FastAPI, Flask) for ML services.