Generative AI Engineer

Were 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

1 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)

2 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

3 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

4 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

5 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

6 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

• 45 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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