Machine Learning Engineer

About the Role:

Machine Learning Engineer

Key Responsibilities:

• Design, build, and deploy scalable machine learning models and pipelines.
  
• Collaborate with data scientists to transition models from research to production.
  
• Develop and maintain data preprocessing, feature engineering, and model training pipelines.
  
• Evaluate model performance using appropriate metrics and continuously optimize for accuracy and efficiency.
  
• Integrate ML models into production systems via APIs, microservices, or MLOps workflows.
  
• Automate training, testing, and deployment processes using CI/CD and orchestration tools.
  
• Monitor model performance in production and retrain as necessary to maintain accuracy.
  
• Stay updated with the latest trends, research, and technologies in AI and machine learning.
  
• Collaborate cross-functionally with product, engineering, and data teams to deliver data-driven solutions.

Preferred Qualifications:

• Experience with

  deep learning, NLP, or computer vision

  applications.
• Background in deploying ML models at scale for real-time or batch inference.
  
• Knowledge of

  A/B testing, feature stores, and model monitoring systems

  .
• Familiarity with

  data visualization tools

  (Tableau, Power BI, Plotly).
• Contribution to open-source ML/AI projects is a plus.