Join a dynamic team in the Freight and Logistics sector as a Machine Learning Engineer. You'll work with both structured and unstructured data to build and maintain AI models, ensuring they are efficient and effective.
Innovative and collaborative, with a focus on leveraging AI in logistics.
As a Machine Learning Engineer at Datacentrix, you will be part of a team dedicated to enhancing the Freight and Logistics sector through AI solutions. Your primary responsibility will be to work with both structured and unstructured data, preparing and cleaning it to create features for AI models. This role is ideal for someone who enjoys tackling complex data challenges and is passionate about implementing machine learning solutions in a practical setting.
In your day-to-day work, you will collaborate with cross-functional teams, including business stakeholders, developers, and data engineers. This collaboration is crucial as you will need to understand the business needs and translate them into technical requirements. You will also implement MLOps practices, ensuring that the models you develop are continuously monitored and updated as needed.
Key responsibilities include: • Preparing and cleaning data for AI models • Engineering features from various data sources • Implementing version control and CI/CD for machine learning models • Monitoring model performance and detecting drift • Responsible retraining of models to maintain accuracy
To succeed in this role, familiarity with MLOps, version control systems like Git, and cloud deployment patterns is essential. While certifications such as Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate are preferred, they are not mandatory. If you are a proactive problem-solver with a strong foundation in machine learning and data engineering, this position could be a great fit for you.
You'll be taken to the original listing on PNet to apply.