Greater Noida Uttar Pradesh Deep learning engineer Jobs – 120 Open Jobs Today

Sr. Associate AI Data Engineer
EXL Service —Noida, Uttar Pradesh
- Full-time
- Azure
- Data analysis skills
- Master's degree
14d
Sr. AI Engineer 4B
Genpact India Pvt. Ltd. —Noida, Uttar Pradesh
- Full-time
- Hybrid work
- Azure
- Computer Science
- English
Quick apply
1d
Technical Lead - SCALA
Fusionpact Career —Noida, Uttar Pradesh
- Computer Science
- DevOps
- Databases
Quick apply
Systems Integration Senior Specialist Advisor
NTT Ltd —Noida, Uttar Pradesh
- Full-time
- Azure
- Doctoral degree
- Computer Science
Architect
Alight —Noida, Uttar Pradesh
- Computer Science
- DevOps
- Java
- Health insurance
- Paid sick time
Senior AL/ML Engineer
WebSenor InfoTech —Noida, Uttar Pradesh
- Full-time
- Remote
- Azure
- Computer Science
- Master's degree
Quick apply
2h
Senior AI/ML-Generative AI
WebSenor InfoTech —Noida, Uttar Pradesh
- Full-time
- Hybrid work
- Azure
- Computer Science
- DevOps
Quick apply
1h
Sr. Staff Software Engineer- Eng - JAVA + AI
UKG (Ultimate Kronos Group) —Noida, Uttar Pradesh
- Azure
- Computer Science
- Software troubleshooting
5h

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Sr. Associate AI Data Engineer

EXL Service -
Noida, Uttar Pradesh

Apply Now

Job details

Full-time
14 days ago

Qualifications

CI/CD
Azure
Law
Enterprise Software
Data analysis skills
Master's degree
SQL
AWS
Continuous integration
Natural language processing
APIs
ETL
Data science
Flask
AI
Python

Full job description

Job Description: Key Responsibilities

Design and develop LLM-based solutions for business use cases (e.g., chatbots, summarisation, document intelligence).
Build and optimise RAG (Retrieval Augmented Generation) pipelines including data ingestion, embeddings, and retrieval.
Implement prompt engineering techniques (prompt design, chaining, optimisation).
Develop backend services/APIs for AI applications using Python frameworks (FastAPI / Flask / Streamlit) .
Integrate LLM solutions with enterprise systems and structured/unstructured data sources.
Apply basic guardrails and evaluation techniques to improve response quality and reduce hallucinations.
Collaborate with cross-functional teams to ensure data quality, model performance, and deployment readiness .

Must-Have Skills

Experience

2–4 years total experience , with exposure to AI/ML, NLP, or Data Engineering projects
Hands-on experience or strong learning exposure to LLM / GenAI use cases (projects, POCs, academic work, or professional)

LLM / GenAI & Agentic Engineering

Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
Experience with:
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures

Core Engineering

Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
Deep data analysis experience and handling large volume of data
Fabric/Azure Databricks/Snowflake data engineering integration skills
Good exposure to:
- Cloud platforms (Azure/AWS/GCP)
- SQL

Data / AI Foundations (Mandatory)

Prior experience in one or more:

Data Engineering (ETL/ELT, pipelines, orchestration)
Data Science / ML lifecycle (especially NLP)

Good-to-Have

Exposure to agentic workflows or tool calling concepts
Basic knowledge of fine-tuning / prompt tuning (LoRA, PEFT – optional exposure)
Experience with Azure OpenAI / Azure AI Search or similar stacks
Awareness of enterprise AI considerations (data security, privacy, governance)

Responsibilities: Key Responsibilities

Design and develop LLM-based solutions for business use cases (e.g., chatbots, summarisation, document intelligence).
Build and optimise RAG (Retrieval Augmented Generation) pipelines including data ingestion, embeddings, and retrieval.
Implement prompt engineering techniques (prompt design, chaining, optimisation).
Develop backend services/APIs for AI applications using Python frameworks (FastAPI / Flask / Streamlit) .
Integrate LLM solutions with enterprise systems and structured/unstructured data sources.
Apply basic guardrails and evaluation techniques to improve response quality and reduce hallucinations.
Collaborate with cross-functional teams to ensure data quality, model performance, and deployment readiness .

Must-Have Skills

Experience

2–4 years total experience , with exposure to AI/ML, NLP, or Data Engineering projects
Hands-on experience or strong learning exposure to LLM / GenAI use cases (projects, POCs, academic work, or professional)

LLM / GenAI & Agentic Engineering

Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
Experience with:
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures

Core Engineering

Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
Deep data analysis experience and handling large volume of data
Fabric/Azure Databricks/Snowflake data engineering integration skills
Good exposure to:
- Cloud platforms (Azure/AWS/GCP)
- SQL

Data / AI Foundations (Mandatory)

Prior experience in one or more:

Data Engineering (ETL/ELT, pipelines, orchestration)
Data Science / ML lifecycle (especially NLP)

Good-to-Have

Exposure to agentic workflows or tool calling concepts
Basic knowledge of fine-tuning / prompt tuning (LoRA, PEFT – optional exposure)
Experience with Azure OpenAI / Azure AI Search or similar stacks
Awareness of enterprise AI considerations (data security, privacy, governance)

Qualifications: Key Responsibilities

Design and develop LLM-based solutions for business use cases (e.g., chatbots, summarisation, document intelligence).
Build and optimise RAG (Retrieval Augmented Generation) pipelines including data ingestion, embeddings, and retrieval.
Implement prompt engineering techniques (prompt design, chaining, optimisation).
Develop backend services/APIs for AI applications using Python frameworks (FastAPI / Flask / Streamlit) .
Integrate LLM solutions with enterprise systems and structured/unstructured data sources.
Apply basic guardrails and evaluation techniques to improve response quality and reduce hallucinations.
Collaborate with cross-functional teams to ensure data quality, model performance, and deployment readiness .

Must-Have Skills

Experience

2–4 years total experience , with exposure to AI/ML, NLP, or Data Engineering projects
Hands-on experience or strong learning exposure to LLM / GenAI use cases (projects, POCs, academic work, or professional)

LLM / GenAI & Agentic Engineering

Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
Experience with:
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures

Core Engineering

Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
Deep data analysis experience and handling large volume of data
Fabric/Azure Databricks/Snowflake data engineering integration skills
Good exposure to:
- Cloud platforms (Azure/AWS/GCP)
- SQL

Data / AI Foundations (Mandatory)

Prior experience in one or more:

Data Engineering (ETL/ELT, pipelines, orchestration)
Data Science / ML lifecycle (especially NLP)

Good-to-Have

Exposure to agentic workflows or tool calling concepts
Basic knowledge of fine-tuning / prompt tuning (LoRA, PEFT – optional exposure)
Experience with Azure OpenAI / Azure AI Search or similar stacks
Awareness of enterprise AI considerations (data security, privacy, governance)

Apply Now

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deep learning engineer jobs in greater noida uttar pradesh

Sr. Associate AI Data Engineer

Sr. AI Engineer 4B

Technical Lead - SCALA

Systems Integration Senior Specialist Advisor

Architect

Senior AL/ML Engineer

Senior AI/ML-Generative AI

Sr. Staff Software Engineer- Eng - JAVA + AI

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