About the Role

We are looking for an Senior AI/ML Engineer with 4+ years of Strong hands-on experience building and deploying production-grade AI systems. The ideal candidate should have robust expertise in Computer Vision, Generative AI, RAG pipelines, Voice AI, and LLM-powered applications, with experience delivering scalable, production-ready solutions across enterprise, healthcare, or SaaS environments

Key Responsibilities

- Design, develop, and deploy production-ready AI/ML and Generative AI applications, Computer Vision solutions.
- Build and optimize LLM-powered applications for real-world business use cases.
- Develop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
- Build Voice AI solutions including speech-to-text (STT), text-to-speech (TTS), conversational AI, and voice-enabled assistants.
- Create and optimize prompt engineering strategies to improve LLM output quality, consistency, and reliability.
- Work with open-source LLMs for inference, fine-tuning, evaluation, and deployment.
- Implement model monitoring, evaluation, guardrails, and performance optimization.
- Collaborate with DevOps and cloud teams for scalable deployments.
- Optimize AI systems for latency, cost, scalability, and production performance.
- Integrate AI services through APIs and enterprise applications.

Required Skills & Experience

- 4+ years of experience in AI/ML engineering and production deployments.
- Strong experience in Python and AI/ML development.
- Hands-on experience with Generative AI and LLM applications.
- Strong hands-on experience in Computer Vision using Python and frameworks such as OpenCV, PyTorch, and TensorFlow.




- Experience with Computer Vision tasks such as object detection, image classification, image segmentation, and feature extraction.
- Familiarity with models and libraries such as YOLO, Detectron2, MMDetection, and torchvision.
- Experience with image preprocessing, data augmentation, model training, evaluation, and inference optimization.
- Exposure to OCR technologies such as Tesseract or EasyOCR and vision-based deep learning models is an advantage.
- Experience building RAG pipelines using:
- Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB, Milvus
- Embeddings and retrieval optimization
- Experience with Prompt Engineering techniques for LLM optimization.
- Experience with Open Source LLMs such as:
- Llama, Mistral, Falcon, Gemma, DeepSeek, Qwen
- Experience with Voice AI technologies:
- Speech-to-Text (Whisper, Deepgram, Google STT)
- Text-to-Speech (ElevenLabs, Azure Speech, Amazon Polly)
- Conversational Voice Agents
- Experience using frameworks/tools:
- LangChain, LangGraph, LlamaIndex, Hugging Face
- Understanding of fine-tuning, model evaluation, inference optimization, and AI observability.
- Experience deploying applications using:
- Docker, Kubernetes, CI/CD
- AWS / Azure / GCP

Preferred Qualifications

- Experience delivering AI solutions for Healthcare, Enterprise, or SaaS platforms.
- Exposure to MLOps practices and model lifecycle management.
- Understanding of AI governance, security, and responsible AI practices.
- Experience integrating AI with APIs and production services.

Nice to Have

- Knowledge of agentic AI workflows and orchestration.
- Experience with monitoring and evaluation frameworks.
- Exposure to multimodal AI applications

Education Qualifications

- B.Tech / M.Tech in CSE / IT / AI&ML; only from good college.

📌 Senior AI/ML Engineer (Hyderabad)
🏢 Quanteon Solutions
📍 Hyderabad