{"id":3303563,"url":"https://alion.io/job/quanteon-solutions-senior-aiml-engineer-2","title":"Senior AI/ML Engineer","company":{"id":3807895,"name":"Quanteon Solutions","domain":"quanteonsolutions.com","url":"https://alion.io/company/quanteon-solutions","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":1500000,"max":3500000,"currency":"INR","period":"year","gross":true,"usd_annual":36943},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Computer Vision","optional":false},{"name":"Data Augmentation","optional":false},{"name":"Deepgram","optional":false},{"name":"DeepSeek","optional":false},{"name":"Detectron2","optional":false},{"name":"Docker","optional":false},{"name":"EasyOCR","optional":false},{"name":"ElevenLabs","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Falcon","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Gemma","optional":false},{"name":"Image Segmentation","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Mistral","optional":false},{"name":"MMDetection","optional":false},{"name":"OCR","optional":false},{"name":"OpenCV","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Torchvision","optional":false},{"name":"Weaviate","optional":false},{"name":"Whisper","optional":false},{"name":"YOLO","optional":false},{"name":"AI Agents","optional":true},{"name":"AWS","optional":true},{"name":"FastAPI","optional":true},{"name":"Machine Learning","optional":true},{"name":"Multimodal AI","optional":true}],"status":"live","first_seen_at":"2026-10-26T12:06:44Z","employer_posted_date":null,"last_verified_at":"2026-10-26T12:06:44Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"About the Role\nWe are looking for an AI/ML Engineer with 4+ years of Strong hands-on experience building and deploying production-grade AI systems. The ideal candidate should have strong 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\n\nKey Responsibilities\nDesign, develop, and deploy production-ready AI/ML and Generative AI applications, Computer Vision solutions.\nBuild and optimize LLM-powered applications for real-world business use cases.\nDevelop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.\nBuild Voice AI solutions including speech-to-text (STT), text-to-speech (TTS), conversational AI, and voice-enabled assistants.\nCreate and optimize prompt engineering strategies to improve LLM output quality, consistency, and reliability.\nWork with open-source LLMs for inference, fine-tuning, evaluation, and deployment.\nImplement model monitoring, evaluation, guardrails, and performance optimization.\nCollaborate with DevOps and cloud teams for scalable deployments.\nOptimize AI systems for latency, cost, scalability, and production performance.\nIntegrate AI services through APIs and enterprise applications.\n\nRequired Skills & Experience\n4+ years of experience in AI/ML engineering and production deployments.\nStrong experience in Python and AI/ML development.\nHands-on experience with Generative AI and LLM applications.\nStrong hands-on experience in Computer Vision using Python and frameworks such as OpenCV, PyTorch, and TensorFlow.\nExperience with Computer Vision tasks such as object detection, image classification, image segmentation, and feature extraction.\nFamiliarity with models and libraries such as YOLO, Detectron2, MMDetection, and torchvision.\nExperience with image preprocessing, data augmentation, model training, evaluation, and inference optimization.\nExposure to OCR technologies such as Tesseract or EasyOCR and vision-based deep learning models is an advantage.\nExperience building RAG pipelines using:\nVector Databases: Pinecone, Weaviate, FAISS, ChromaDB, Milvus\nEmbeddings and retrieval optimization\nExperience with Prompt Engineering techniques for LLM optimization.\nExperience with Open Source LLMs such as:\nLlama, Mistral, Falcon, Gemma, DeepSeek, Qwen\nExperience with Voice AI technologies:\nSpeech-to-Text (Whisper, Deepgram, Google STT)\nText-to-Speech (ElevenLabs, Azure Speech, Amazon Polly)\nConversational Voice Agents\nExperience using frameworks/tools:\nLangChain, LangGraph, LlamaIndex, Hugging Face\nUnderstanding of fine-tuning, model evaluation, inference optimization, and AI observability.\nExperience deploying applications using:\nDocker, Kubernetes, CI/CD\nAWS / Azure / GCP\n\nPreferred Qualifications\nExperience delivering AI solutions for Healthcare, Enterprise, or SaaS platforms.\nExposure to MLOps practices and model lifecycle management.\nUnderstanding of AI governance, security, and responsible AI practices.\nExperience integrating AI with APIs and production services.\n\nNice to Have\nKnowledge of agentic AI workflows and orchestration.\nExperience with monitoring and evaluation frameworks.\nExposure to multimodal AI applications\n\nEducation Qualifications\nB.Tech / M.Tech in CSE / IT / AI&ML only from good college.\nSkills\nGenerative AI, Agentic AI, Computer Vision, Generative AI (GenAI), Voice AI, Machine Learning (ML), Deep Learning, Python, FastAPI, Amazon Web Services (AWS), Retrieval Augmented Generation (RAG), Open-source LLMs, Fine-tuning LLMs, Large Language Models (LLM), Langchain, LangGraph, FAISS, ChromaDB, Vector 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