Machine Learning Lead - Natural Language Processing

• Algorithm Development:

  Design and program integrated software algorithms to structure, analyze, and use data in both structured and unstructured environments.

• Statistical Modelling:

  Apply experimental methodologies, statistics, optimization, probability theory, and machine learning to create tools, statistical models, and algorithms using general-purpose software and statistical languages.

• Insights and Optimization:

  Develop descriptive, diagnostic, predictive, and prescriptive insights and algorithms to improve product and system performance.

• ML and Statistical Techniques:

  Use techniques such as decision trees, logistic regression, Bayesian analysis, NLP, and other methods to design algorithms that enhance product quality, data accuracy, and system performance.

• Code Implementation:

  Translate algorithms and technical specifications into efficient, production-ready code using modern programming languages like Python

• Debugging:

  Implement programming practices, perform testing and debugging, and increase system efficiency.

• Documentation:

  Create comprehensive documentation and maintenance procedures for implemented systems and algorithms.

• Generative AI Applications:

  Develop and implement generative AI technologies for applications such as content generation, conversational systems, and interactive user experiences.

• Emerge Technologies:

  Adapt machine learning methodologies to areas like artificial intelligence, image processing, and other modern technologies to promote solutions.

• Cloud-Based Solutions:

  Deploy scalable solutions in cloud-based environments (e.g., AWS, Azure, and GCP).

Education:

Technical Skills:

• Proficiency in machine learning and natural language processing (NLP).
• Experience with software fundamentals, data structures, and algorithms.
• Hands-on experience with CI/CD pipelines, distributed systems, and cloud-based software.
• Expertise in generative AI and building conversational systems.
• Classification systems, sentiment analysis, NLP, and entity extraction
• Computer vision, OCR, and content extraction from images, PDFs, and HTML
• 7+ years of experience with custom models and ensembles
• Experience in cloud-based environments (e.g., AWS, Azure, GCP)
• Expertise in generative AI and building conversational systems

Software Development:

Experience with object-oriented design principles, common design patterns, and best practices.