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Machine Learning Engineer

Global leader in trusted and transformative intelligence, providing enriched data, insights, analytics and workflow solutions across knowledge, research and innovation.
Machine Learning
Senior Software Engineer
Hybrid
1,000 - 5,000 Employees
5+ years of experience
AI · Enterprise SaaS

Description For Machine Learning Engineer

Clarivate, a global leader in trusted intelligence and analytics, is seeking a Machine Learning Engineer to join their Technology team. This role offers an exciting opportunity to work in a cross-cultural environment while focusing on cutting-edge ML technologies. The position involves working with the Intellectual Property (IP) group's data science team, collaborating with product and technology teams worldwide.

The ideal candidate will be responsible for deploying and monitoring machine learning models in production, designing scalable infrastructure, and driving MLOps innovation. You'll work with state-of-the-art tools and technologies including cloud platforms, containerization, and MLOps frameworks. The role requires a strong background in machine learning, data engineering, and DevOps practices.

Working at Clarivate means being part of a company that transforms how global innovations are discovered, protected, and commercialized. The position offers the flexibility of hybrid work arrangements and the opportunity to work with globally distributed teams. You'll be contributing to world-class products and services that make a real impact in the field of intellectual property and innovation.

This is an excellent opportunity for a seasoned ML engineer who wants to work with interesting IP data challenges while being part of a company that values innovation and technical excellence. The role offers a balance of technical depth and business impact, with opportunities to influence the direction of ML infrastructure and practices.

Last updated 2 minutes ago

Responsibilities For Machine Learning Engineer

  • 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
  • Design and manage scalable infrastructure for model training and deployment
  • Automate repetitive tasks to improve efficiency
  • Ensure infrastructure meets security and compliance standards
  • Stay updated with latest trends in MLOps
  • Drive innovation within the team to enhance MLOps capabilities

Requirements For Machine Learning Engineer

Python
Kubernetes
  • Bachelor's or master's degree in computer science, Engineering, or related field
  • 5+ years of experience in machine learning, data engineering, or software development
  • Experience in building data pipelines, data cleaning, and feature engineering
  • Knowledge of programming languages (Python, R) and version control systems (Git)
  • Experience with MLOps tools and platforms (Kubeflow, MLflow, Airflow)
  • Knowledge of DevOps principles, CI/CD pipelines, and infrastructure as code
  • Experience with cloud platforms (AWS, GCP, Azure)
  • Familiarity with container orchestration tools like Kubernetes

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