Large Language Model Architect

Overview

Architect large language models that can process and generate natural language, designing neural network parameters trained on large quantities of unlabeled text data. Serve as an SME, lead model architecture work, and coordinate with stakeholders within an AI-powered tech talent role.

What you'll do

• Lead the development and implementation of innovative language model architectures to meet evolving project requirements.
• Design and structure advanced language models capable of understanding and generating human-like text.
• Plan neural network configurations and manage the training process using extensive datasets.
• Continuously evaluate and refine model architectures to enhance performance across natural language processing tasks.
• Collaborate with cross-functional teams to align model capabilities with project goals.
• Coordinate with stakeholders to ensure alignment of model design with business objectives and technical feasibility.
• Facilitate knowledge sharing and mentorship within the team.
• Formulate real-world problems into practical, efficient and scalable AI and machine learning solutions.
• Develop and implement machine learning algorithms, models and computational systems, and design and build scalable data pipelines to support model training and production with DevOps and MLOps.
• Customize and apply deep learning and Gen AI models for various use cases based on business needs, data availability, and system and infrastructure requirements, including edge device and HPC.
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production.
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.
• Justify the value of model approaches in business problems.
• Engage in research and development of new AI and high-performance compute algorithms, models and simulations.

What you'll need

• Must have: proficiency in Databricks Unified Data Analytics Platform.
• Minimum 7.5 years of experience in Databricks Unified Data Analytics Platform.
• Bachelor's degree or equivalent.
• Minimum 5 years of experience as a machine learning engineer or scientist, deploying models in production at scale, including monitoring, alerting, automatic bug filing and auditing.
• Minimum 5 years of experience applying theoretical foundations of computer science, including computer system architecture, system engineering and programming.
• Minimum 3 years of experience in distributed computing systems and architecture, which may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks.
• Minimum 2 years of experience building and deploying AI/ML based software to a cloud environment.
• Proficiency in Python and Python-based AI/ML frameworks and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).
• Experience working with language models like LLM APIs and optimizing their usage for specific applications.
• Experience with the following programming languages: Python, C++, Java, R, SQL.
• Strong written and verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders.
• Strong client-facing skillsets in a consulting environment.
• Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams.
• Entrepreneurial mindset with curiosity and passion for emergent tech and driving innovation.
• Ability to troubleshoot and resolve complex technical challenges related to model training and deployment.
• Strong expertise in designing and optimizing neural network architectures for natural language processing applications.
• Experience handling large-scale datasets and implementing efficient data processing pipelines.
• Familiarity with distributed computing environments and cloud-based analytics platforms.
• Educational qualification: 15 years full-time education.

Nice to have

• Experience with Machine Learning (ML) and Data Science.
• MS or PhD in a related field (computer science, engineering, etc.).

Details

• Location: Hyderabad office.