Noida Sector 62 Noida Uttar Pradesh Senior database developer Jobs – 109 Open Jobs Today

Campus-Competent
HCLTech —Noida, Uttar Pradesh
- Azure
- Master's degree
- SQL
2h
Full-Stack Developer Intern (Python & React)
Fusionpact Career —Noida, Uttar Pradesh
- Full-time
- Remote
- Azure
- System design
- Databases
Quick apply
SAP ABAP Intern
BlackBull Technosoft —Noida, Uttar Pradesh
- ₹3,92,908.27 - ₹16,69,186.48 a year
- Full-time
- Computer Science
- Software troubleshooting
- Master's degree
- Flexible schedule
Quick apply
14d
Full Stack Developer
The Growing Graph —Faridabad, Haryana
- ₹10,000 - ₹15,000 a month
- Full-time
- Project management
- JavaScript
- APIs
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PHP- Laravel Intern
Eglogics Softech —Noida, Uttar Pradesh
- ₹5,000 - ₹10,000 a month
- Full-time
- Computer Science
- Master's degree
- Databases

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Campus-Competent

HCLTech -
Noida, Uttar Pradesh

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Job details

Fresher | Internship
2 hours ago

Qualifications

TensorFlow
Azure
Operating systems
Data structures
NumPy
Git
Master's degree
SQL
Pandas
AWS
Database management
Bachelor's degree
Machine learning
Deep learning
SDKs
GitHub
Data science
Keras
AI
Python

Full job description

Noida, Uttar Pradesh
Job Summary

About the Role
We are seeking enthusiastic and highly motivated Fresher AIML Developer to join our innovative technology team. This role is designed for recent B. Tech graduates specializing in Artificial Intelligence, Machine Learning and Data Science. You will contribute to the entire lifecycle of our Software and AI products, from data collection and cleaning to model development, deployment, and monitoring. This is an excellent opportunity to apply your academic knowledge to real-world business challenges and grow into a skilled professional in the rapidly evolving field of AI.

Key Responsibilities

Key Responsibilities
•

Model Development and Training:
o
Work under supervision to implement, train, and validate various Machine Learning models (e.g., Regression, Classification, Clustering, Neural Networks), SLMs and LLMs
o
Assist in feature engineering and selection to improve model performance.
•

Coding and Implementation:
o
Write clean, efficient, and well-documented code in Python for data processing and model implementation.
o
Collaborate with senior engineers to integrate models into production environments.
•

Evaluation and Reporting:
o
Perform rigorous model evaluation using relevant metrics and statistical analysis.
o
Document development processes, results, and findings clearly.

Skill Requirements

Required Qualifications & Skills (The Non-Negotiables)
•
Education: B. Tech/ master’s degree in a relevant field (CSE/IT/EC/AI/ML/DL)
2
•
Designs, builds, fine-tunes, and deploys AI systems powered by Large Language Models (LLMs), Vision-Language Models (VLMs), and multimodal architectures
•
Academic Performance: Strong academic record (mention a minimum required CGPA/percentage if applicable).
•
Programming Proficiency: Demonstrated hands-on experience and proficiency in Python (including libraries like NumPy, Pandas, Numba and Scikit-learn).
•
Core Concepts: Solid understanding of fundamental Operating Systems, Database Management System, Data Structures and Algorithms.
•
Database Knowledge: Basic proficiency in SQL for data querying and manipulation.
•
AIML Foundations: Strong theoretical understanding of key Machine Learning algorithms, Deep Learning, Generative AI, LLMs, statistical & probabilistic modeling, and data engineering + visualization techniques.

Other Requirements

Preferred Skills (The Value-Adds)
•
GenAI Frameworks: Hands-on with Langchain, Langgraph, LLAMAIndex, LangServe, ADK, Nemo, etc. Copilots, Agent SDK, OpenAI Assistants
•
Deep Learning Frameworks: Familiarity with at least one major Deep Learning framework (e.g., TensorFlow, PyTorch, or Keras). And skill to Develop multimodal AI systems combining text, images, documents, audio, and structured data.
•
GenAI Skill: Prompt engineering, RAG, fine-tuning, and agentic workflows, Build end-to-end GenAI pipelines including data ingestion, embeddings, retrieval, inference, and feedback loops
•
Version Control: Experience with Git and GitHub for collaborative code development.
•
Cloud Exposure: Awareness of cloud computing platforms (e.g., AWS, Azure, or GCP) and their data/ML services along with MLOps/LLMOps
•
Project Experience: Completion of relevant academic projects, internships, or Kaggle competitions showcasing practical application of AIML skills.

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