Machine Learning Engineer

Company Description

iPerformX is transforming the training industry with advanced technologies, delivering personalized, data-driven solutions to improve learning and performance outcomes. With over two decades of experience, iPerformX has developed cognitive and behavioral training programs that leverage real-time data, biometric insights, and learning patterns to create customized learning paths. Our adaptive training ecosystem integrates artificial intelligence (AI), machine learning (ML), data analytics, and performance management to optimize the training experience for students and instructors. The iPerformX platform supports performance analytics, AI-driven curriculum optimization, predictive modeling, personalized learning channels, and many more capabilities that ensure measurable and impactful results.

Role Description

This is a full-time on-site role for a Machine Learning Engineer located in Tampa, FL. The Machine Learning Engineer will be responsible for designing, developing, and deploying machine learning models and algorithms. Daily tasks include working with pattern recognition, neural networks, and AI algorithms to build predictive models, analyzing real-time and historical data, and contributing to the development of adaptive training solutions. Collaboration with cross-functional teams to improve and implement machine learning solutions is also a key responsibility.

Qualifications

• Strong knowledge in some of the following: NLP, DNNs, as well as classic statistical and learning models such as decision forests and genetic algorithms respectively.
• Advanced skills in Python, with close familiarity of Pandas, PyTorch, LangChain, Flask and Scikit-Learn
• Proficiency with Docker
• Proficiency in writing high-performance deterministic algorithms.
• Experience in optimizing and deploying machine learning models.
• Bachelor's or Master's degree in Computer Science, or a related field.
• Strong problem-solving skills and ability to work collaboratively in a team environment.
• Experience with cloud-based ecosystems and big data platforms is advantageous.