Data Engineer

Role:
• Collaborate with cross-functional teams to understand business requirements and translate them into machine learning solutions
• Design and develop robust machine learning models and algorithms that solve complex business problems
• Design and develop data and analytics solutions that sit atop vast datasets
• Clean, preprocess, and analyze data to ensure its suitability for machine learning applications
• Implement end-to-end machine learning pipelines, from data collection and feature engineering to model training and deployment
• Select appropriate machine learning techniques and algorithms based on the problem's requirements and constraints
• Perform exploratory data analysis and generate insights to guide model development
• Evaluate and fine-tune machine learning models for performance, accuracy, and reliability
• Deploy machine learning models into production environments, ensuring scalability and maintainability
• Collaborate with technical team to integrate machine learning solutions into applications
• Stay up-to-date with the latest advancements in machine learning and recommend innovative approaches to enhance our capabilities
• Document and communicate machine learning solutions, findings, and insights to technical and non-technical stakeholders
• Additional tasks as required

All About You:
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
• Proven experience as a machine learning engineer, working on complex machine learning projects
• Strong programming skills in languages like Python, R, or similar
• Solid understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques
• Hands-on experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
• Proficiency in data preprocessing, feature engineering, and data visualization
• Experience with cloud platforms such as AWS, Azure, or GCP for deploying machine learning models
• Familiarity with version control systems (e.g., Git) and collaborative development practices
• Strong problem-solving skills and ability to troubleshoot and optimize machine learning models
• Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders
• Proven ability to work in a collaborative team environment and drive projects to completion