At a Glance
- Tasks: Monitor and maintain machine learning models in production, ensuring reliability and performance.
- Company: Join a forward-thinking tech company focused on ML innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement potential.
- Why this job: Be at the forefront of ML technology and make a real impact on production systems.
- Qualifications: Strong Python skills and experience with ML model deployment and monitoring.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking an experienced MLOps Engineer to join our team, focusing on the deployment, monitoring, and maintenance of machine learning models in production environments. This role does not involve model development or end-user support but is critical to ensuring the reliability and performance of our ML platforms. The successful candidate will also be responsible for managing API endpoints and overseeing model deployment workflows to ensure seamless integration and scalability.
Key Responsibilities
- Monitor ML model endpoints and overall platform health using tools like Grafana and Domino Data Lab.
- Respond to incidents and alerts, perform code fixes, manage incidents internally and manage changes through ServiceNow.
- Interface directly with Domino Data Lab support to resolve model platform-related issues.
- Deploy and maintain ML models in production environments.
- Ensure models are properly integrated into automated pipelines and meet standards.
- Collaborate with data scientists and engineers to ensure smooth handoff from model development to production.
- Maintain and support ML pipelines, ensuring stability and scalability.
- Continuously optimize pipeline performance, resource usage, and automation.
Automation & Tooling
- Implement automation for deployment and monitoring tasks.
- Contribute to platform improvements.
Required Skills & Experience
- Extensive experience in Python programming.
- Strong experience with ML model deployment and production monitoring.
- Working knowledge of core data science concepts, such as model evaluation metrics, overfitting, data drift, and feature importance.
- Experience with Grafana for monitoring and alerting.
- Good to have hands-on experience with Domino Data Lab platform.
- Solid understanding of CI/CD pipelines, version control, containerization, and orchestration.
- Ability to communicate effectively with internal and external stakeholders.
- Excellent troubleshooting and incident management skills.
Machine Learning Engineer in London employer: Intuition IT – Intuitive Technology Recruitment
Join a forward-thinking company that values innovation and collaboration, where as a Machine Learning Engineer, you will play a pivotal role in ensuring the reliability of our cutting-edge ML platforms. Our supportive work culture fosters continuous learning and professional growth, offering opportunities to enhance your skills while working alongside talented professionals in a dynamic environment. Located in a vibrant tech hub, we provide a unique advantage with access to industry-leading resources and networking opportunities, making us an excellent employer for those seeking meaningful and rewarding careers.
Contact Details:
Intuition IT – Intuitive Technology Recruitment Recruitment Team
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We think you need these skills to ace Machine Learning Engineer in London
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