Vdart Software Services Pvt Ltd
https://www.vdartinc.com/About
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Jobs at Vdart Software Services Pvt Ltd
.NET
C#✔️ 8+ years of overall software development experience
✔️ 5+ years of relevant experience in Azure Integration using Logic Apps, Azure Functions, and .NET C#
✔️ Work closely with the Integration Architect. Understand and review requirement with Integration Architect for Biztalk/Foresight/Azure interface integrations.
✔️ Implement (Code in Azure Logic Apps, C#, Azure functions), modify integrations interface as per the interface specification.
✔️ Perform and document unit testing for implemented interfaces.
✔️ Assess and manage risk with leads and discuss possible recommendations.
✔️ Follow best practices, standards, and policies in implementation.
✔️ Perform code review sessions, and follow the coding guidelines.
✔️ Perform and support Integration & UAT testing; fix issues and defects.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Job Description:
We are hiring freshers for our International Chat Support Team to assist customers via chat, resolve queries, and provide exceptional service.
Requirements:
- Any Graduate (Freshers welcome).
- Excellent written English skills.
- Strong problem-solving ability.
- Basic computer knowledge.
- Willingness to work in rotational shifts.
Perks:
- Competitive salary + incentives.
- Career growth opportunities.
- Friendly work environment.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Machine Learning (ML)
PythonJob Descriptions:
1. Job Requirement
We are seeking a highly skilled Senior Generative AI Developer to join our AI/ML team. This role focuses on leveraging cutting-edge Generative AI (GenAI) technologies to drive innovation and efficiency in software development and business processes. The ideal candidate will work on advanced techniques such as Retrieval-Augmented Generation (RAG), document chunking, and data embedding across multiple vector databases. They will collaborate closely with cross-functional teams to design, implement, and optimize AI-driven solutions, with exposure to cloud-native AI platforms like Amazon Bedrock and Microsoft Azure OpenAI considered a plus.
Responsibilities:
- Develop and deploy GenAI-based applications to solve complex business problems.
- Implement RAG frameworks to enhance information retrieval and response accuracy.
- Design and optimize document chunking strategies tailored to specific data types and use cases.
- Build and manage data embeddings using various vector databases for high-performance similarity searches.
- Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
- Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.
- Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.
2. Required Technical Skillsets
Mandatory Skills:
- Proficiency in Generative AI frameworks and technologies like
- Prompt Engineering – creating specific prompts to guide LLM outputs
- Fine Tuning and Few-Shot learning – Adapting LLMs for domain-specific tasks.
- Retrieval-Augmented Generation (RAG) – Combining LLMs with external data retrieval systems
- Text-to-Text Transfer Transformation (T5) – Framework for translating tasks into text forms.
- Expertise in designing and implementing chunking strategies for diverse datasets.
- Strong knowledge of data embedding techniques and working experience with vector databases like Pinecone, Weaviate, or Milvus.
- Solid programming skills in Python, with experience in AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
- Familiarity with cloud platforms and services for AI/ML workloads (AWS or Azure).
- Experience with API integration for AI services and building scalable applications.
Desirable Skills:
- Hands-on experience with Amazon Bedrock and/or Microsoft Azure OpenAI services.
- Knowledge of natural language processing (NLP) techniques and large language model (LLM) fine-tuning.
- Exposure to different chunking strategies, including overlap and semantic segmentation.
- Understanding of DevOps practices for deploying and managing AI models in production.
- Strong problem-solving and analytical skills with a focus on delivering value-driven solutions.
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