Machine Learning Engineer

Machine Learning EngineerLeading SaaS organisationHybrid workingMarket leading SaaS organisation is seeking a highly skilled and motivated Machine Learning Engineer to join their team. As a Machine Learning Engineer, you will be responsible for designing, implementing, and maintaining machine learning models that address real-world challenges. You will collaborate closely with data scientists, software engineers, and business stakeholders to deploy scalable AI solutions and improve the overall performance of our data-driven products.Key Responsibilities:Model Development: Design, build, and evaluate machine learning models, including supervised, unsupervised, and reinforcement learning approaches.Data Processing: Clean, preprocess, and transform large datasets to make them suitable for model training and prediction.Algorithm Optimization: Implement and optimize machine learning algorithms to meet performance and accuracy goals.Model Deployment: Develop robust systems for deploying machine learning models into production environments, ensuring scalability and reliability.Collaboration: Work with data scientists to convert prototypes into production-ready models, and collaborate with software engineers to integrate machine learning models into existing systems.Model Monitoring: Monitor and maintain models after deployment, ensuring they remain accurate and adapt to changing data distributions (model drift detection).Continuous Improvement: Stay updated on new machine learning techniques, tools, and best practices to ensure cutting-edge solutions.Documentation: Document processes, models, and tools to maintain high levels of reproducibility and collaboration.Experience:Proven experience in developing, deploying, and maintaining machine learning models in production environments.Experience working with a range of machine learning techniques (regression, classification, clustering, neural networks, etc.).Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and traditional machine learning libraries (e.g., Scikit-learn, XGBoost).Technical Skills:Strong programming skills in Python, R, or another relevant language.Experience with data manipulation and analysis tools like Pandas, NumPy, or similar.Proficiency with machine learning frameworks and libraries (TensorFlow, PyTorch, Scikit-learn, etc.).Experience with cloud platforms (Azure) for model training and deployment.Knowledge of containerization and orchestration tools like Docker and Kubernetes.Understanding of database systems and experience with SQL/NoSQL databases.Familiarity with big data tools such as Hadoop, Spark, or Kafka is a plus.Soft Skills:Strong problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.Team player with excellent communication skills and the ability to work in a fast-paced environment.Strong attention to detail and a passion for innovation.Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field. PhD is a plus.Please apply today for immediate consideration