SENIOR MACHINE LEARNING ENGINEER – Legal Space
HYBRID – 3 Days a week in central London office
Up to 100,000
COMPANY:
We are working with a leadingcompany in the legal space who are investing heavily in the AI/ML space. They are looking for a new ML Engineer to join the team and work closely with the existing Data Science team to help deploy models into production.
Given the industry space, the team have had a particular focus on LLM's.
ROLE:
- Design, build, and deploy scalable machine learning models to solve complex business problems.
- Implement and maintain robust MLOps pipelines, ensuring efficient CI/CD processes for machine learning.
- Automate the deployment and monitoring of models in production to ensure continuous performance and stability.
- Collaborate closely with data scientists, helping them move models from development to production seamlessly.
- Monitor and troubleshoot machine learning models in production environments, ensuring uptime and accuracy.
- Develop best practices around model versioning, testing, and governance.
- Stay up-to-date with the latest developments in ML engineering, cloud services, and automation tools.
REQUIREMENTS:
- 4+ years of experience in machine learning engineering, with a strong focus on productionizing ML models and MLOps.
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow).
- Proven track record of delivering ML models that solve real-world business challenges at scale.
- Excellent communication skills with the ability to work effectively in cross-functional teams.
If this role looks of interest, please reach out to Joseph Gregory
