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 : Snowflake Data Warehouse, Microsoft Azure Data Services
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.)
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 process natural language. The workday includes analyzing model performance, refining parameters, and collaborating with various teams to integrate these models into broader applications. Continuous innovation and problem-solving are key aspects, as the architect shapes the future capabilities of language-based artificial intelligence systems.
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 project goals.
- Facilitate knowledge sharing and mentorship within the team to foster professional growth.
- Coordinate cross-functional efforts to align model development with organizational objectives.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Google Cloud Data Services.
- Good To Have Skills: Experience with Snowflake Data Warehouse, Microsoft Azure Data Services.
- Strong expertise in designing and optimizing neural network architectures for natural language processing.
- Experience with large-scale data processing and management in cloud environments.
- Ability to analyze and improve model training processes using extensive unlabeled datasets.
- Familiarity with integrating language models into production systems and ensuring their scalability and reliability.
Additional Information:
- The candidate should have minimum 12 years of experience in Google Cloud Data Services.
- This position is based at our Kolkata office.
- A 15 years full time education is required.
