- Company Name
- Kingfisher plc
- Job Title
- Senior Machine Learning Engineer
- Job Description
-
**Job title:** Senior Machine Learning Engineer
**Role Summary:**
Design, develop, and operationalise scalable machine learning solutions that drive customer and business outcomes. Work closely with cross‑functional engineering, product, and architecture teams to ensure models are robust, efficient, and production‑ready, while continuously improving ML pipelines and tooling.
**Expectations:**
- Deliver end‑to‑end ML projects from prototype to production.
- Write clean, maintainable Python code and adhere to best engineering practices.
- Own model performance monitoring, optimisation, and continuous improvement.
- Collaborate proactively with product owners, data engineers, and infrastructure teams.
- Share knowledge and mentor junior teammates to foster a collaborative culture.
**Key Responsibilities:**
- Build and optimise machine learning models using classical and modern techniques (e.g., NLP, deep learning).
- Deploy models into production environments and maintain deployment pipelines.
- Develop, maintain, and automate data pipelines (SQL, ETL) for model training and evaluation.
- Implement and upgrade tooling, CI/CD workflows, and containerisation solutions for ML workloads.
- Monitor model drift, performance metrics, and trigger re‑training or remediation actions.
- Translate business requirements into data‑driven solutions and validate outcomes with stakeholders.
- Conduct knowledge‑sharing sessions and contribute to engineering best‑practice documentation.
**Required Skills:**
- Strong foundation in computer science fundamentals: data structures, algorithms, software design.
- Proficiency in Python, with experience using Pandas, scikit‑learn, Jupyter, and related libraries.
- Experience with SQL, data pipelines, and ETL/ELT processes.
- Hands‑on knowledge of machine learning lifecycle: model training, evaluation, tuning, monitoring, and deployment.
- Familiarity with version control (Git), CI/CD pipelines, and container technologies (Docker, Kubernetes).
- Ability to apply statistical concepts for data interpretation and model assessment.
- Excellent communication and collaboration skills in multidisciplinary teams.
- Comfortable working in an agile, iterative development environment.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related technical field.
- Relevant professional certifications (e.g., TensorFlow Developer, AWS Certified Machine Learning – Specialty) are a plus but not mandatory.