Sr. Principal Machine Learning Engineer

OPENTEXT 
OpenText is a global leader in information management, where innovation, creativity, and collaboration are the key components of our corporate culture. As a member of our team, you will have the opportunity to partner with the most highly regarded companies in the world, tackle complex issues, and contribute to projects that shape the future of digital transformation.

 

 

The Opportunity: 

 

As a Machine Learning Engineer at OpenText, you'll embark on an exhilarating journey, facilitating and creating groundbreaking machine learning models and algorithms and developing software products. Your mission? To unravel intricate business puzzles and craft tailored, one-of-a-kind solutions for our valued clientele. Your canvas? A dynamic lab and sandbox environment where innovation knows no bounds. Collaboration is key as you join forces with diverse teams, weaving machine learning and generative AI magic into the fabric of our enterprise solutions. Your creations will not only meet but exceed the most exacting standards of performance, reliability, and scalability.

 

But this role offers more than just challenges; it's an invitation to help shape the future. By contributing to cutting edge technology, your work will leave an indelible mark on global businesses. Welcome to the forefront of innovation, where the intersection of curiosity, creativity, and technology sparks limitless possibilities.

 

You Are Great At:

 

• Collaborate with product managers, software engineers, and data scientists to understand business requirements and translate them into machine learning solutions.
• Design, develop, and deploy machine learning models and algorithms that enhance the functionality and intelligence of our enterprise software products.
• Explore and analyze large datasets to identify patterns, trends, and insights that can inform the development of robust machine learning models.
• Implement and optimize machine learning pipelines for training, testing, and deployment of models in production environments.
• Work on feature engineering, data preprocessing, and model evaluation to ensure the accuracy and effectiveness of machine learning models.
• Stay abreast of the latest advancements in machine learning and artificial intelligence, and apply relevant techniques to solve real-world problems.
• Collaborate with cross-functional teams to integrate machine learning capabilities seamlessly into existing and new software products.
• Conduct code reviews, provide constructive feedback, and contribute to the continuous improvement of development processes.
• Maintain documentation for machine learning models, algorithms, and implementation details to ensure transparency and knowledge sharing within the team.
• Stay informed about industry best practices, emerging trends, and advancements in machine learning, and actively contribute to the company's knowledge base.

 

What It Takes: 

 

Required:

 

• Hold a Master’s degree or Ph.D. in Computer Science, Applied Mathematics, Statistics, or a related field with a strong emphasis on Natural Language Processing (NLP) and proficiency in Large Language Models (LLMs).
• Accumulate 3+ years of professional experience, including a significant time dedicated to relevant and hands-on work in Machine Learning, with a specific focus on NLP and LLMs.
• Proven track record in developing and deploying advanced Deep Learning models, particularly those tailored for NLP tasks and Large Language Models.
• Demonstrate substantial knowledge and practical experience in implementing Deep Learning models for extracting insights from textual data, Natural Language Understanding, Text Classification, and Document Analysis, all within the context of NLP and LLMs.
• Possess excellent communication skills, encompassing both verbal and written proficiency, to effectively convey complex concepts and findings related to NLP and Large Language Models.
• Proven expertise in utilizing cloud-based environments such as AWS, Azure, or GCP

 

Desired:

• Solid foundational understanding of machine learning and statistical concepts, with a focus on Natural Language Processing (NLP) and Large Language Models (LLMs).
• Proficiency in deep learning frameworks commonly used in NLP tasks, such as TensorFlow and PyTorch.
• Hands-on experience in at least two projects involving Large Language Models and other deep learning applications.
• A minimum of 5+ years of expertise in Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), particularly in the context of NLP, with the ability to develop custom models for various deep learning tasks.
• At least 5+ years of practical experience