Senior Machine Learning Engineer – NLP

Our innovative NLP team is looking for a Senior Machine Learning Engineer - NLP to spearhead the development and enhancement of our cutting-edge AI models. This pivotal role focuses on the entire lifecycle of AI model development, from data collection and model pre-training to fine-tuning, evaluation and deployment. The ideal candidate will bring hands-on industrial experience with these processes and similar tasks, demonstrating a deep understanding of the complexities involved in creating and serving models that can understand and interpret human language at an advanced level.You will play a pivotal role in our San Ramon, CA headquarters, enjoying a hybrid work model that blends collaboration and flexibility with three office days per week (Mondays, Wednesdays, Thursdays). 

Key Responsibilities:

• Collect, organize, and pre-process extensive datasets suitable for distribution training NLP models, ensuring the data is of high quality and representative of various use cases.
• Evaluate the performance of AI models, including GenAI models, using rigorous testing methodologies to ensure they meet or exceed industry standards.
• Continuously monitor the performance of deployed ML/DL/LLMs models, and iteratively improve them based on feedback.
• Collaborate closely with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate AI models into product offerings.
• Stay up-to-date with the latest advancements in GenAI technologies and methodologies to ensure the use of best practices in model development and deployment.

Requirements:

• 5+ years of on-hands experience in Machine Learning Engineer related roles.
• Strong programming skills in Python, with extensive experience using NLP libraries and frameworks such as TensorFlow, PyTorch, spaCy, HuggingFace Transformers, etc.
• Experience with Java is an asset.
• Experience with Generative AI, Large Language Models, Distributed Deep Learning Model training, and prompt tuning.
• Strong background in MLOps methodologies, with a proven ability to guide the implementation of tools and best practices for model deployment and continuous improvement.
• Solid understanding of machine learning principles and their application to NLP tasks.
• Proficiency in NLP techniques and models such as transformer architectures and their applications.
• Excellent problem-solving skills and creativity in finding solutions to complex challenges in NLP.
• Advanced degree (Master’s or PhD) in Computer Science, Artificial Intelligence, or a related field, with a focus on NLP.
• This position requires the ability to be on-call.

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