Large Language Model Architect

Overview

Architect large language models that process and generate natural language, designing neural network parameters trained on large quantities of unlabeled text data, and lead the team on related AI/ML solutions for enterprise clients.

What you'll do

• 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.
• Engage in research and development of new AI and high-performance compute algorithms, models and simulations to solve complex business problems at client sites.
• 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.
• Collaborate with business and technical teams, including users, business owners, engineers, architects and UI designers, to achieve end-to-end project goals and integrate into production.
• Lead the development and implementation of innovative language model architectures to meet evolving project requirements.
• Evaluate model performance using relevant metrics and implement improvements accordingly.
• Facilitate knowledge sharing and mentorship within the team.
• Coordinate cross-functional efforts to integrate language models into broader systems and applications.

What you'll need

• Machine Learning (ML) proficiency (must have).
• Minimum 7.5 years of experience is required.
• 15 years full time education.
• Bachelor's Degree or equivalent.
• Minimum of 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 of 5 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming.
• Minimum of 3 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks.
• Minimum of 2 years of experience in 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.

Nice to have

• Snowflake Data Warehouse skills.
• Microsoft Azure Data Services skills.
• MS or PhD in a related field (computer science, engineering, etc.).
• Familiarity with distributed computing environments and cloud-based platforms to enhance model scalability and deployment.

Details

• Based at the Bengaluru office.
• Team lead role: expected to be an SME, manage the team, be responsible for team decisions, and provide solutions across multiple teams.