ML Engineer

We are working with a large Utilities/Energy client looking to bring on several experienced Machine Learning Engineers to support ML initiatives as part of a broader contact center transformation program. You will join an existing agile delivery team focused on modernizing customer engagement, service operations, and agent experience using data and machine learning. There is scope to add additional engineers as the program progresses. This role suits someone who is hands on, comfortable working across the full ML lifecycle, and experienced in deploying machine learning solutions that support real world operational use cases. This is an initial 6-month contract engagement with a strong view to extend. Rates are competitive and dependent on experience, with full time hours. We engage contractors via W2 or personal LLC only and cannot work with C2C third party vendors. What you will be doing • Building, training, and deploying machine learning models to support contact center use cases • Working with structured and unstructured data such as call metadata, transcripts, and customer interaction data • Partnering closely with data engineering, data science, and product teams to operationalise models • Developing and maintaining ML pipelines for training, inference, and monitoring • Supporting model performance, reliability, and scalability in production environments What we are looking for • Strong experience as a Machine Learning Engineer delivering models into production • Strong Python experience and familiarity with common ML libraries • Experience deploying and operating ML workloads in cloud environments • Understanding of the full ML lifecycle from data ingestion to deployment • Experience working in agile, delivery focused teams Nice to have • Experience with NLP, speech analytics, or text based ML use cases • Exposure to contact center platforms or customer service analytics • Experience with deep learning frameworks such as PyTorch or TensorFlow • Exposure to GenAI or LLM based customer interaction use cases Why this role • High impact work supporting customer facing transformation • Modern data and ML stack within a regulated utilities environment • Opportunity to work with experienced data, ML, and engineering teams • Flexible engagement model