NAZZTEC
Website:
nazztec.com
Job details:
🚀 We’re Hiring: Senior NLP / AI Engineer
📍 Location: Noida
🧑 💻 Mode: Hybrid
💼 Experience: 4+ Years (Relevant)
🕒 Notice Period: Immediate to 30 Days (Max)
📄 Employment Type: Full-Time
🌟 About the Role
We are looking for a highly skilled Senior NLP / AI Engineer to design, build, and scale cutting-edge AI systems powering Translation, Transliteration, ASR, OCR, LLM, and RAG solutions for enterprise and government clients.
This role demands strong expertise in production-grade NLP and speech systems, deep learning model optimization, AI infrastructure, and end-to-end ownership of large-scale deployments. You will play a critical role in shaping AI capabilities used across platforms, chatbots, voice-bots, and enterprise AI products.
🔑 Key Responsibilities
1️⃣ AI Model Development & Training
- Train, fine-tune, and deploy models across:
- Multilingual Neural Machine Translation (NMT)
- Transliteration (Indian Languages)
- Speech-to-Text (ASR – Whisper, NVIDIA NeMo, Indic-ASR)
- Text-to-Speech (TTS)
- Large Language Models (LLMs)
- Embedding models for RAG
- Build multilingual models supporting 20+ Indian languages
- Create, preprocess, augment datasets and manage large-scale training
- Benchmark models using BLEU, chrF++, WER, CER, and custom metrics
- Convert models to optimized inference formats (CTranslate2, Faster-Whisper, INT4/INT8/AWQ)
2️⃣ Model Optimization for Production
- Reduce model size using quantization and pruning
- Optimize inference latency for real-time workloads
- Improve GPU/CPU utilization and memory efficiency
- Build scalable inference pipelines for translation, ASR, and RAG systems
3️⃣ Audio & Video Processing Systems
- Develop advanced audio transcription & translation pipelines
- Implement real-time STT systems for Indic languages
- Build video subtitle extraction and SRT translation workflows
- Integrate diarization, language detection, summarization, and cross-lingual translation
4️⃣ RAG & LLM-Based Systems
- Design multilingual Retrieval-Augmented Generation (RAG) pipelines
- Build and manage vector databases and embedding models
- Implement document indexing, chunking, parsing, and hybrid search
- Integrate open-source LLMs (Llama, Gemma, Qwen, etc.) for chatbot and voice-bot systems
5️⃣ Infrastructure & Server Management
- Manage AI/ML GPU servers on AWS & GCP
- Optimize infra cost via GPU scheduling and server consolidation
- Implement monitoring, logging, auto-restart, and fail-safe mechanisms
- Deploy high-availability APIs for translation, ASR, OCR, and chatbots
- Troubleshoot GPU drivers, CUDA, and NVIDIA environments
6️⃣ Cross-Functional Ownership
- Collaborate with Sales, Ops, and Tech teams to deliver large enterprise projects
- Handle production incidents, escalations, and mission-critical deployments
- Maintain detailed documentation for APIs, workflows, and deployments
- Build internal tools, FAQs, and automation to reduce support dependency
✅ Required Skills & Experience
🔧 Technical Skills
- 4–5 years of experience in production NLP / ML systems
- Strong expertise in NLP, Speech, Deep Learning, Generative AI
- Hands-on experience with:
- Python, PyTorch, TensorFlow
- ASR, TTS, Transformers, open-source LLMs
- CTranslate2, Faster-Whisper, ONNX Runtime
- vLLM, SGLang, LLM quantization techniques
- FAISS, Pinecone (Vector Databases)
- Docker, FastAPI, Linux
- AWS / GCP GPU infrastructure
- Strong experience in multilingual NLP, especially Indian languages
- Experience creating datasets and training models from scratch
🤝 Soft Skills
- Strong ownership and accountability
- Excellent communication and documentation skills
- Ability to independently research, prototype, and deploy systems
- Strong prioritization and deadline management
- Ability to handle high-pressure production environments
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