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Senior Machine Learning Engineer

Our client is embarking on a major digital transformation project, centred on migrating its on-premises data warehouse to an advanced cloud solution, with Databricks and other complementary tools forming the core of this new data infrastructure. This shift is designed to position the company at the technological forefront, optimising scalability, efficiency and innovation across its operations.

To this end, and to support this strategic change, our client is creating a new “Senior Machine Learning Engineer” role aimed at bridging IT and business operations, focusing on establishing a standardised and efficient approach to MLOps. This person will be a key figure in developing and embedding MLOps best practices, facilitating cross-functional collaboration and ensuring that machine learning capabilities are seamlessly integrated into the companies’ cloud ecosystem.

The role:

The primary objective of the Senior Machine Learning Engineer role is to establish a strategic approach to data handling and machine learning operations, enabling scalable, efficient, and reliable ML workflows across the business. This will be achieved through both technical execution and mentorship, ensuring MLOps becomes an integral part of business operations.

Key responsibilities:

  1. Adoption of MLOps Best Practices
  2. Mentorship and Team Leadership
  3. Model Optimization and Performance Enhancement
  4. Migration of Models to Databricks Platform
  5. Development of MLflow Pipelines
  6. Implementation of CI/CD Pipelines

Skills:

  • Candidates should have a strong understanding of machine learning algorithms and techniques
  • Proficiency in Python, R is a plus
  • Experience with MLOps tools and frameworks (mlflow preferred)
  • Knowledge of cloud platforms (Azure preferred)
  • Excellent communication and interpersonal skills
  • Experience with optimising models for performance and scalability
  • Nice to have: experience with Databricks and its ML capabilities
  • Nice to have: Certifications in ML and/or MLOps

If you would like to learn more about this role, please contact Lancelot for more information.


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