Machine Learning Engineer

Your responsibilities, Health, Safety & Environment:, Complete mandatory HSE courses and implement any recommended safety actions efficiently., Be a consistent role model in relation to safety practices with a commitment to the importance of safety, Performance & Delivery:, Optimize model performance through hyperparameter tuning, feature engineering, and algorithm selection., Collaborate with data scientists to translate prototypes into production-ready solutions., Design and implement scalable machine learning pipelines for training, validation, and deployment., Develop APIs and services to integrate machine learning models into enterprise applications., Ensure robustness and reliability of ML systems through unit testing, integration testing, and CI/CD practices., Monitor model performance in production and implement retraining strategies as needed., Leverage cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes) for scalable deployment., Apply best practices in software engineering, including version control, code reviews, and documentation., Manage infrastructure for data ingestion, model training, and inference at scale., Implement model governance practices, including auditability, reproducibility, and compliance., Collaborate with cross-functional teams including DevOps, software engineers, and product managers., Stay current with advancements in ML engineering tools, frameworks, and deployment strategies., Utilize a broad range of technologies including deep learning frameworks (e.g., TensorFlow, PyTorch), MLOps tools (e.g., MLflow, Kubeflow), and distributed computing (e.g., Spark, Ray)., Communicate results effectively to both technical and non-technical stakeholders.