Cyient
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Hyderabad · On-site · 3-6 Yrs · Aug 26
Information Technology Support Services · 10000+ Employees · Hyderābād, India
Cyient is a global engineering and technology solutions company. As a Design, Build, and Maintain partner for leading organizations worldwide, we take solution ownership across the value chain to help clients focus on their core, innovate, and stay ahead of the curve. We leverage digital technologies, advanced analytics capabilities, and our domain knowledge and technical expertise, to solve complex business problems. With over 15,000 employees globally, we partner with clients to operate as part of their extended team in ways that best suit their organization’s culture and requirements. Our industry focus includes aerospace and defense, healthcare, telecommunications, rail transportation, semiconductor, geospatial, industrial, and energy.
Hiring: Engineering
What employees say
+ very nice company, stick to the actual hours and are supportive
− Pay might be less but experience is worth it
More reviews on the company profile.
Interview experience · Senior AMS Verification Engineer
There were two rounds of interview, 1. Project details and few technical questions 2. Hiring manager took interview asking AMS flow and basic circuit design questions Most of the questions are mid level difficulty not t
Average difficulty · Bengaluru · 445 reports
More interview insightsJob description
Overview
Senior Software Engineer – Python & AI (3–5 Years Experience) Experience • 4+ years of software development experience.
Responsibilities
- Develop and maintain Python-based applications and APIs.
- Build AI-powered solutions using LLMs and Generative AI technologies.
- Design and implement RAG-based systems and AI agents.
- Integrate databases and external services.
- Optimize and deploy AI models for production environments.
Qualifications
- Strong Python programming skills
- FastAPI
- RESTful API development
- CRUD operations
- Database integration (PostgreSQL/MySQL/MongoDB)
- NumPy
- Pandas
- PyAutoGUI
- Fundamentals of Machine Learning, Deep Learning, and AI
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Generative AI
- Local LLM deployment and management
- Embeddings and Vector Databases
- Agentic AI
- Model Fine-tuning
- Model Quantization and Optimization
- Knowledge of Docker, Git, and cloud platforms (Azure/AWS).
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