Salary Profiles
Company
Title
Experience
Annual Salary
School
Skills
Turing
Palo Alto
4.4yrs

Base: ₹42.0lakhs

Stocks: -

Bonus: -

CTC:₹42.0lakhs

Mcp Llmops Graphrag Mlops Fastapi Software Development (Show More) Custom Gpts Chatbot Development Large Language Model Operations (Llmops) Neo4j Retrieval-augmented Generation (Rag) Search And Retrieval Multi-agent Systems Crewai Algorithm Design Cohere Weaviate Reranking Semantic Search Annoyindex Deep Learning Pytorch Tensorflow Reinforcement Learning Cross-functional Team Leadership Artificial Intelligence (Ai) K-nearest Neighbors (Knn) Approximate Nearest Neighbors (Ann) Hierarchical Navigable Small World (Hnsw) Vector Databases Sparse Search, Dense Search And Hybrid Search Requirements Gathering Gemini Ai Agents Langgraph Langchain Rag Docker Streamlit Generativeai Large Language Model Web Development Forecasting Optical Character Recognition (Ocr) Systems Design Sampling Linear Models Dashboard Building Prediction Experimental Design Project Leadership Hyperparameter Tuning Google Analytics Data Visualization Market Research Chatgpt Data Analytics Interpersonal Skills Leadership Large Language Models (Llm) Prompt
23.6yrs
Python Team Problem Solving Technical Documentation Google Workspace Windows Os Configuration Project Delivery (Show More) Transmission Control Protocol (Tcp) Inventory Management It Procurement Research Skills Microsoft Access Customer Communication Attention To Detail Cloud Security Specifications Business Analysis Workload Prioritization Documentation Motor Vehicle Lan-wan Analytical Skills Windows System Administration Performance Analysis Quality Assurance It Infrastructure Management Security Information Security Customer Satisfaction Root Cause Problem Solving Customer-focused Selling It Escalation Customer Experience Management Reliability Management Implement Migration Strategy Critical Thinking Define Generative Ai Explain How Generative Ai Works Describe Generative Ai Model Types Describe Generative Ai Applications Generativeai Databases Solid-state Drive (Ssd) Hard Drives Windows Server Active Directory Group Policy Client Relations High Performance Computing (Hpc) Sql Microsoft Azure Linux Infrastructure Git

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Frequently asked questions
How much do Generativeai employees make?

Employees who know Generativeai earn an average of ₹47.3lakhs, mostly ranging from ₹45.7lakhs per year to ₹52.5lakhs per year based on 2 profiles. The top 10% of employees earn more than ₹51.4lakhs per year.

What is the average salary of Generativeai?

Average salary of an employee who know Generativeai is ₹47.3lakhs.

What is the median salary offered who know Generativeai?

The median salary approximately calculated from salary profiles measured so far is ₹47.3lakhs per year.

How is the age distributed among employees who know Generativeai?

This group has a predominantly younger workforce. 50% of employees lie between 21-26 yrs . 50% of the employees fall in the age group of > 41 yrs .

Frequently asked questions
How much do Generativeai employees make?

Employees who know Generativeai earn an average of ₹47.3lakhs, mostly ranging from ₹45.7lakhs per year to ₹52.5lakhs per year based on 2 profiles. The top 10% of employees earn more than ₹51.4lakhs per year.

What is the average salary of Generativeai?

Average salary of an employee who know Generativeai is ₹47.3lakhs.

What is the median salary offered who know Generativeai?

The median salary approximately calculated from salary profiles measured so far is ₹47.3lakhs per year.

How is the age distributed among employees who know Generativeai?

This group has a predominantly younger workforce. 50% of employees lie between 21-26 yrs . 50% of the employees fall in the age group of > 41 yrs .

Salary Brackets
Percentage
40-50 lakhs 40-50 lakhs
Percentage : 50
> 50 lakhs > 50 lakhs
Percentage : 50
Age Brackets
Percentage
21-26 yrs 21-26 yrs
Percentage : 50
> 41 yrs > 41 yrs
Percentage : 50
Skills
Trending
generativeai
100 %
active directory
0 %
ai agents
0 %
algorithm design
0 %
analytical skills
0 %
annoyindex
0 %
approximate nearest neighbors (ann)
0 %
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