Leading AI/ML Engineer for Large Scale Model Deployment
2 weeks ago
We are seeking a highly skilled Machine Learning Engineer to join our team at Harnham. This role involves designing, building, and deploying scalable machine learning models to solve complex business problems in the legal space.
About the RoleThis is a hybrid role that requires 3 days of work in our central London office per week. The successful candidate will have up to £100,000 annual salary and be part of a leading company investing heavily in AI/ML technologies.
Key Responsibilities- Design and Deploy ML Models: Create and deploy scalable machine learning models using Python and ML libraries such as TensorFlow, PyTorch, or Scikit-learn.
- MLOps Pipelines: Implement and maintain robust MLOps pipelines to ensure efficient CI/CD processes for machine learning.
- Model Monitoring and Maintenance: Automate the deployment and monitoring of models in production environments to ensure continuous performance and stability.
- Collaboration with Data Scientists: Work closely with data scientists to help them move models from development to production seamlessly.
- A minimum of 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).
- A 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.
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