Machine Learning Engineer

We are looking for a ML Ops Engineer to join our Technology team at Clarivate.

You will get the opportunity to work in a cross-cultural work environment while working on the latest web technologies with an emphasis on user-centered design.

About You (Skills & Experience Required)

• Bachelors or masters degree in computer science, Engineering, or a related field.

• 3+ years of experience in machine learning, data engineering, or software development.
• Good experience in building data pipelines, data cleaning, and feature engineering is essential for preparing data for model training.
• Knowledge of programming languages (Python, R), and version control systems (Git) is necessary for building and maintaining MLOps pipelines.
• Experience with MLOps-specific tools and platforms (e.g., Kubeflow, MLflow, Airflow) can streamline MLOps workflows.
• DevOps principles, including CI/CD pipelines, infrastructure as code (IaaC), and monitoring is helpful for automating ML workflows.
• Experience with atleast one of the cloud platforms (AWS, GCP, Azure) and their associated services (e.g., compute, storage, ML platforms) is essential for deploying and scaling ML models.
• Familiarity with container orchestration tools like Kubernetes can help manage and scale ML workloads efficiently.

It would be great if you also had,

• Experience with big data technologies (Hadoop, Spark).
• Knowledge of data governance and security practices.
• Familiarity with DevOps practices and tools.

What will you be doing in this role?

Model Deployment & Monitoring:

• Oversee the deployment of machine learning models into production environments.
• Ensure continuous monitoring and performance tuning of deployed models.
• Implement robust CI/CD pipelines for model updates and rollbacks.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Communicate project status, risks, and opportunities to stakeholders.
• Provide technical guidance and support to team members.

Infrastructure & Automation:

• Design and manage scalable infrastructure for model training and deployment.
• Automate repetitive tasks to improve efficiency and reduce errors.
• Ensure the infrastructure meets security and compliance standards.

Innovation & Improvement:

• Stay updated with the latest trends and technologies in MLOps.
• Identify opportunities for process improvements and implement them.
• Drive innovation within the team to enhance the MLOps capabilities.

About the Team

You would be part of our incredible data science team of Intellectual property (IP) group & work closely with product and technology teams spreads across various locations worldwide. You would be working on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services.

Hours of Work

This is a permanent position with Clarivate.9 hours per day including lunch break. you should be flexible with working hours to align with globally distributed teams and stakeholders.