Responsibility of / Expectations from the Role
EXP :8 TO 10
- 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
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)
