Machine Learning Engineer,VP

Join us as a Machine Learning Engineer In this role, you’ll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms Day-to-day, you’ll make sure that models and algorithms work effectively in a production environment while promoting data literacy education with business stakeholders If you see opportunities where others see challenges, you’ll find that this solutions-driven role will be your chance to solve new problems and enjoy excellent career development What you’ll do Your daily responsibilities will include you collaborating with colleagues to design and develop advanced machine learning products which power our group for our customers. You’ll also codify and automate complex machine learning model productions, including pipeline optimisation. We’ll expect you to transform advanced data science prototypes and apply machine learning algorithms and tools. You’ll also plan, manage, and deliver larger or complex projects, involving a variety of colleagues and teams across our business. You’ll Also Be Responsible For Understanding the complex requirements and needs of business stakeholders, developing good relationships and how machine learning solutions can support our business strategy Working with colleagues to productionise machine learning models, including pipeline design and development and testing and deployment, so the original intent is carried over to production Creating frameworks to ensure robust monitoring of machine learning models within a production environment, making sure they deliver quality and performance Understanding and addressing any shortfalls, for instance, through retraining Leading direct reports and wider teams in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and Scrum outcomes The skills you’ll need To be successful in this role, you’ll need to have a good academic background in a STEM discipline, such as Mathematics, Physics, Engineering or Computer Science. You’ll also have the ability to use data to solve business problems, from hypotheses through to resolution. We’ll look to you to have experience of at least twelve years with machine learning on large datasets, as well as experience building, testing, supporting, and deploying advanced machine learning models into a production environment using modern CI/CD tools, including git, TeamCity and CodeDeploy. You’ll Also Need A good understanding of machine learning approaches and algorithms such as supervised or unsupervised learning, deep learning, NLP with a strong focus on model development, deployment, and optimization Experience using Python with libraries such as NumPy, Pandas, Scikit-learn, and TensorFlow or PyTorch An understanding of PySpark for distributed data processing and manipulation with AWS (Amazon Web Services) including EC2, S3, Lambda, SageMaker, and other cloud tools. Experience with data processing frameworks such as Apache Kafka, Apache Airflow and containerization technologies such as Docker and orchestration tools such as Kubernetes Experience of building GenAI solutions to automate workflows to improve productivity and efficiency Show more Show less