ML Data Analytics

Description

Summary:

We are seeking a talented Machine Learning Engineer to develop efficient, data-driven AI systems that enhance our predictive automation capabilities. The ideal candidate will be highly skilled in statistics and programming, with the ability to confidently assess, analyze, and organize large datasets. Additionally, the candidate should be proficient in executing tests and optimizing machine learning models and algorithms.

Role

As a machine learning engineer, your primary responsibilities include:

• Develop and implement data-driven ML predictive models to advance intelligent automation and reporting
• Assess, analyze, and organize large datasets to extract meaningful insights
• Execute tests to validate machine learning models and algorithms
• Optimize machine learning models for improved performance and accuracy
• Collaborate with cross-functional teams to integrate machine learning solutions into existing systems
• Monitor and maintain machine learning models to ensure ongoing accuracy and efficiency
• Research and stay updated on the latest advancements in machine learning and ML techniques and applications
• Document processes, methodologies, and model performance for transparency and reproducibility
• Troubleshoot and resolve issues related to machine learning model deployment and operation
• Mentor and provide technical guidance to junior engineers, sharing best practices and fostering a culture of continuous learning
  
  

• A bachelors degree or masters degree in computer science, data science, or a related field
• 5+ years of experience in machine learning, data engineering, or software development
• Strong programming skills and proficiency in languages commonly used for ML and related tasks
• Big Data skills and be proficiency in data structures, modeling, and visualization
• Proven background in statistical analysis and data analysis to support model training and evaluation
• Excellent communication skills for working with stakeholders and translating technical concepts
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn); experience with production-quality code
• Strong background in statistics, mathematics, and data science
• Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models at scale is a plus