Data Science Engineer

Data Science Engineer - MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL

We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) to join their team on a permanent basis. this role we be responsible for the design, development and delivery of advanced analytics and AI solutions.

This is a fantastic time to join a top-tier global law firm who have a long-stream of projects in the pipeline alongside a diverse and collaborative team environment.

To be considered for this Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have:

• Ideal but not required law firm experience
• 2-4 years experience within AI/ML positions
• Knowledge of cloud platforms (Ideally Azure)
• AI/ML Frameworks
• Generative AI
• Data engineering knowledge

Solution Delivery

• Design, build, and deploy data science and AI solutions end-to-end, from design and development through testing, release, monitoring, and support.
• Operationalize models with CI/CD pipelines, automated testing, and monitoring, applying MLOps practices such as versioning, retraining, and drift detection (tools: MLflow, Azure ML, Databricks)
• Leverage both open-source frameworks (LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to deliver production ready, scalable AI solutions
• Implement generative AI and advanced analytics features, including embeddings, retrieval-augmented generation, and building AI agents and chat-based solutions.
• Write clean, testable, and well-documented code using modern engineering practices (unit testing, code reviews, API development, Azure DevOps preferred).

Technical Design & Architecture

• Ensure solutions align with enterprise architecture, data governance, and security standards
• Collaborate with enterprise architects, IT, and business stakeholders to validate approaches
• Contribute to lifecycle management practices including model versioning, monitoring, and continuous improvement of delivery processes
• Evaluate and pilot emerging technologies to improve scalability and solution quality.