Machine Learning Infrastructure Specialist
hace 3 días
Company Overview
Founded in 2016 by a small team, Quantexa was built with a vision of enabling better decision making through better data-driven intelligence. Seven years, twelve locations and 700+ employees later we recently gained "Unicorn" status with our Series E funding round.
Role Overview
We are looking for a highly skilled MLOps Engineer to join our overseas team, working in parallel with our existing MLOps team. This individual will focus on developing and maintaining the infrastructure and automation pipelines that support our machine learning models, ensuring that they can be deployed efficiently into production environments.
Job Description
This role will involve close collaboration with data scientists, data engineers, and other MLOps engineers to deliver robust, scalable machine learning pipelines that are optimized for production environments. Model deployment, pipeline automation, monitoring, and maintenance are key responsibilities.
Key Responsibilities
- Collaborate with data scientists to ensure smooth deployment of machine learning models into production environments.
- Automate the deployment of machine learning models using CI/CD pipelines and container orchestration tools like Kubernetes and Docker.
- Ensure proper model versioning, governance, and compliance using tools like MLFlow, Kubeflow, or DVC.
- Build and maintain data and model pipelines for training, validation, deployment, and monitoring.
- Develop automated processes for data validation, feature engineering, and model training.
- Integrate pipelines with distributed data processing frameworks (e.g., Spark, Kafka) to ensure efficient data handling for model training and inference.
- Set up monitoring systems to track model performance and detect issues like model drift, triggering retraining when necessary.
Requirements
To be successful in this role, you should have experience with machine learning model deployment, automation pipelines, and monitoring systems. Familiarity with cloud infrastructure and containerization is also required. Our ideal candidate will have strong problem-solving skills and excellent communication abilities.
Salary
The estimated salary for this position is around £80,000 - £110,000 per annum, depending on location and experience.
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