Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Google Cloud Data Services
Good to have skills : Microsoft Azure Data Services, Snowflake Data Warehouse
Minimum
15 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
AI Powered Tech Talent
As a senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
Develop and implement machine learning algorithms, models, and computational systems design and build scalable data pipelines to support model training and production with DevOps & MLOps
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, 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 along with their applications 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 teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production
Bachelor's Degree or equivalent
Minimum of 7 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 7 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming
Minimum of 5 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 4 years of experience in building and deploying AI/ML based software to a cloud environment.
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.
Experience with the following programming languages: Python, C++, Java, R, SQL
Strong written & 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 a curiosity and passion for emergent tech and driving innovation
MS or PhD in related field preferred (computer science, engineering, etc.)
As a Large Language Model Architect, a typical day involves designing and structuring advanced language models capable of understanding and generating human-like text. This role requires envisioning the architecture of neural networks that are trained on extensive datasets, ensuring the models can effectively interpret and produce natural language. The position demands continuous collaboration with various teams to refine model parameters and optimize performance, while also staying attuned to the evolving landscape of language processing technologies. Creativity and strategic thinking are essential to develop scalable and efficient solutions that meet complex project requirements.
Roles & Responsibilities:
- Expected to be a SME with deep knowledge and experience.
- Should have Influencing and Advisory skills.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Expected to provide solutions to problems that apply across multiple teams.
- Lead the development and implementation of innovative language model architectures to address diverse business needs.
- Mentor and guide team members to foster professional growth and ensure alignment with project goals.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Google Cloud Data Services.
- Good To Have Skills: Experience with Microsoft Azure Data Services, Snowflake Data Warehouse.
- Strong expertise in designing and optimizing neural network architectures for natural language processing tasks.
- Experience with large-scale data processing and management in cloud environments.
- Ability to analyze and improve model performance through parameter tuning and data preprocessing techniques.
- Familiarity with distributed computing frameworks and scalable infrastructure for training large models.
Additional Information:
- The candidate should have minimum 15 years of experience in Google Cloud Data Services.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
