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 : Snowflake Data Warehouse

Good to have skills : Amazon Web Services (AWS), Machine Learning (ML)

Minimum 12 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

AI Powered Tech Talent

As an 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 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 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.)

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 thoughtful planning of neural network configurations and managing extensive datasets to ensure the models perform effectively. The workday includes continuous refinement of model architectures to enhance their ability to process natural language, collaborating with various teams to align on project goals, and overseeing the integration of these models into broader systems. The role demands a balance of creativity and technical insight to develop innovative solutions that push the boundaries of language processing technology.

Roles & Responsibilities:

Expected to be an SME, collaborate and manage the team to perform.
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 scalable language model architectures to meet evolving project requirements.
Facilitate knowledge sharing and mentorship within the team to foster professional growth and technical excellence.
Coordinate cross-functional efforts to ensure seamless integration of language models with existing data infrastructure.

Professional & Technical Skills:

Must To Have Skills: Proficiency in Snowflake Data Warehouse.
Good To Have Skills: Experience with Amazon Web Services (AWS), Machine Learning (ML).
Strong expertise in designing and optimizing data storage and retrieval processes within cloud-based data warehouses.
Ability to analyze large datasets and translate business requirements into technical solutions.
Experience in managing data pipelines and ensuring data quality and security in distributed environments.
Familiarity with neural network architectures and their application in natural language processing tasks.

Additional Information:

The candidate should have minimum 12 years of experience in Snowflake Data Warehouse.
This position is based at our Bengaluru office.
A 15 years full time education is required.