Tinlas Technologies Private Limited

2 Job openings at Tinlas Technologies Private Limited
Data Science Professional hyderabad 1 - 4 years INR 3.0 - 6.0 Lacs P.A. Work from Office Full Time

Data Science Proficient with LLMs like GPT, Gemini and Llama Experienced in frameworks such as LangChain or Semantic Kernel Hands-on experience with prompting on LLMs, preferably demonstrated through a project Familiarity with graph models, retrieval-augmented generation (RAG), or semantic search. Familiarity with agentic frameworks, preferably have done some project work with agentic framework Candidate must have solid grasp of ML and DL fundamentals Knowledgeable in state-of-the-art NLP techniques Programming Language: Candidate must have good hands on the any programming language preferably python, C#, Knowledge of Database SQL, NoSQL or cloud ecosystem like Azure Basic working knowledge of visualization API such as Streamlit etc.

Full Stack Developer / Senior Full Stack Developer / Lead FSD hyderabad 3 - 10 years INR 5.0 - 12.0 Lacs P.A. Work from Office Full Time

Full Stack Developer / Senior Full Stack Developer / Lead FSD Key Responsibilities Design, develop, and maintain full stack applications using .NET (C#, ASP.NET Core, etc.). Build and optimize data pipelines for real-time and batch processing. Integrate Python-based data workflows into cloud-native applications. Collaborate with cross-functional teams to define, design, and ship new features. Ensure the performance, quality, and responsiveness of applications. Implement security and data protection best practices. Participate in code reviews and contribute to continuous improvement. Required Qualifications 3-10 years of professional experience in full stack development using .NET. Proficiency in C#, ASP.NET Core, and Entity Framework. Strong Python skills, especially in data manipulation and automation. Hands-on experience with cloud platforms (Azure, AWS, or GCP). Familiarity with CI/CD pipelines and DevOps practices. Solid understanding of RESTful APIs, microservices, and containerization (Docker/Kubernetes). Exposure to machine learning or data science workflows.