GEN AI Architect

2 days ago


Hyderabad Mumbai Noida, India Tata Consultancy Services Full time ₹ 2,00,00,000 - ₹ 4,00,00,000 per year

SN Required Information Details

1 Role Gen AI Architect

2 Required Technical Skill Set (MustHave) Gen AI / LLM /Agentic AI

4 Desired Experience Range 10 to 20 Yrs

5 Location of Requirement Any

6 IOU-Detail Digital-Manufacturing

Desired Competencies (Technical/Behavioral Competency)

Must-Have
• Gen AI
• Experience in LLMs, Embedding Models, Prompt Engineering
• Knowledge of statistical programming languages like Python
• Good applied statistical skills
• Good knowledge of machine learning algorithms
• Proficiency in handling imperfections in data & generating insights and patterns.
• Experience with Data Visualization Tools
• Fine tuning of LLM
• Evaluation Framework (RAGAS, ROUGE, BLUE Scrore)
• Autoencoding model (Encoder: ROBERTA/ BERT/ DistilBERT)
• Langsmith framework
• Autoregressive model (Decoder: GPT/ BLOOM/ LLama/ Mistral/ Claude/ CodeGen/ OPT/ PaLM
• RAG/Multimodal Architecture using Langchain/ LlamIndex
• MCP Architecture
• Experience Agentic AI Framework ( Crew AI, AutoGen, LangGraph, Google AVD etc. )
• Experience in Model deployment, LLMOps, Scalability and Performance
• Fine tuning of LLM
• AI ML exp.
• Candidate has exp. in Transformer Architecture (Encoder and decoders)
• Knowledge Graph implementation (If anyone has created knowledge graph, that's good)

Good-to-Have
• Excellent Communication Skills
• Strong Software Engineering Background (Productionizing the models)
• Hands-on experience with data science tools
• Problem-solving aptitude
• Analytical mind and great business sense

SN Responsibility of / Expectations from the Role

1
• Data mining or extracting usable data from valuable data sources.
• Using machine learning tools to select features, create and optimize predictive models.
• Carrying out preprocessing of structured and unstructured data
• Enhancing data collection procedures to include all relevant information for developing analytic systems.
• Processing, cleansing, and validating the integrity of data to be used for analysis.

  • Analyzing large amounts of information to find patterns and solutions.
    • Developing prediction systems and machine learning algorithms
    • Ability to use LLMs to build GenAI powered solutions.
    • Presenting results in a clear manner
    • Propose solutions and strategies to tackle business challenges.
    • Collaborate with Business and IT teams.
    • Designing and developing machine learning and deep learning systems
    • Knowledge of productionizing the ML and DL applications and monitoring


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