Machine Learning Engineer

What role you will play in team: Design, develop, and deploy machine learning models to improve fraud detection and risk management systems.

What you will do: Collaborate with engineers and data scientists to build and maintain machine learning pipelines, and evaluate model performance.

Key responsibility:

• Design, develop, and deploy machine learning models for fraud detection, risk assessment, and other applications.
• Develop and maintain machine learning pipelines using tools such as TensorFlow or PyTorch.
• Evaluate model performance and identify areas for improvement.
• Collaborate with engineers and data scientists to build and maintain machine learning infrastructure.
  
• Stay up-to-date on the latest advancements in machine learning.

Required Qualification and Skills:

• Master's degree or Ph.D. in Computer Science, Machine Learning, or a related field.
• 3+ years of experience in developing and deploying machine learning models.
• Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
• Excellent problem-solving and communication skills.

Benefits Included:

• Competitive salary and benefits package.
• Opportunities for professional development and career advancement.
• A collaborative and innovative work environment.
• Access to cutting-edge technology and resources.
• A chance to make a significant impact on a global company.

A Day in the Life: A typical day involves designing, building, testing, and deploying machine learning models to address real-world business problems.