Machine Learning Infrastructure Developer
hace 5 días
About Us
At Quantexa, we're driven by a passion for innovation and excellence. Our team is built on the foundation of discovery, where collaboration and creativity come together to create meaningful relationships with our clients.
Vision & Mission
We strive to enable better decision-making through data-driven intelligence. Founded in 2016, our vision has taken us from a small team to a global presence, with over 700 employees across 47 nationalities speaking more than 20 languages.
Our Analytics Teams
As part of our Analytics teams, you'll be working on building, deploying, and maintaining AI models that underpin our platform. This includes expertise in Graph-based models and NLP models. We're looking for an experienced MLOps Engineer to join our overseas team and collaborate closely with data scientists, data engineers, and other MLOps engineers to deliver robust machine learning pipelines optimized for production environments.
Key Responsibilities:
- Model Deployment: Collaborate with data scientists to ensure smooth deployment of machine learning models into production environments, automate deployment using CI/CD pipelines and container orchestration tools like Kubernetes and Docker, and ensure proper model versioning, governance, and compliance using tools like MLFlow, Kubeflow, or DVC.
- Pipeline Automation: Build and maintain data and model pipelines for training, validation, deployment, and monitoring, develop automated processes for data validation, feature engineering, and model training, and integrate pipelines with distributed data processing frameworks (e.g., Spark, Kafka) to ensure efficient data handling for model training and inference.
- Monitoring & Maintenance: Set up monitoring systems to track model performance and detect issues like model drift, work with cloud infrastructure to scale models and ensure high availability in production environments, and contribute to troubleshooting and resolution of issues with models in production.
About You
To succeed in this role, you should have a strong background in software development, experience with machine learning and automation, excellent problem-solving skills, and proficiency in programming languages such as Python and Java. As an ideal candidate, you will have a strong understanding of containerization, CI/CD pipelines, and DevOps practices. Familiarity with cloud platforms like AWS, Azure, or Google Cloud is also highly desirable.
Salary Information
The estimated salary range for this position is £80,000 - £120,000 per annum, depending on your level of experience and qualifications.
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