Hire Offshore Machine Learning Engineer

Unlock the Potential of AI: Hire Offshore Machine Learning Engineers for Intelligent Solutions and Competitive Advantage

Role:

Collaborate with data scientists and business stakeholders to understand business requirements and identify opportunities for ML solutions Collect, process, and analyze large datasets to build and train ML models using frameworks such as TensorFlow, PyTorch, or Scikit-learn Develop and deploy ML models into production environments, such as building RESTful APIs or deploying models on cloud platforms like AWS or Azure Monitor and maintain ML models in production, including retraining models and performing model performance evaluations Optimize ML models for performance, scalability, and cost-effectiveness, such as using distributed computing techniques or model compression Stay up-to-date with the latest tools and technologies in machine learning and deep learning

Responsibilities:

Writing clean, efficient, and maintainable code that meets technical specifications and industry standards

• Collaborate with data scientists and business stakeholders to understand business requirements and identify opportunities for ML solutions, such as developing a customer churn prediction model.

• Collect, process, and analyze large datasets to build and train ML models using frameworks such as TensorFlow, PyTorch, or Scikit-learn, such as developing a computer vision model for image classification.

• Develop and deploy ML models into production environments, such as building RESTful APIs or deploying models on cloud platforms like AWS or Azure, to allow integration of the models with other applications or services.

• Monitor and maintain ML models in production, including retraining models and performing model performance evaluations, to ensure that the model is still accurate and up-to-date.

• Optimize ML models for performance, scalability, and cost-effectiveness, such as using distributed computing techniques or model compression, to ensure that the model is efficient and scalable.

• Stay up-to-date with the latest tools and technologies in machine learning and deep learning, such as experimenting with new algorithms or exploring new frameworks.