NLP AI Engineer

Role:
Senior NLP/AI Engineer

Experience: 3+ year

Job Type:
Full-Time

Mode:
Hybrid

Location:
Noida

Key Responsibilities
• AI Model Development & Training

Train, finetune, and deploy models across multiple domains:
Multilingual Neural Machine Translation (NMT), Adaptive Translation Systems
Multilingual Transliteration models (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.
Perform dataset creation, preprocessing, augmentation, and large-scale training.
Conduct model benchmarking using chrf++, BLEU, WER, CER, and custom evaluation metrics.
Convert models to optimized inference formats (CTranslate2, Faster-Whisper, AWQ/INT4/INT8 quant).
• Model Optimization for Production
Reduce model sizes through quantization and pruning.
Optimise inference speed improvements for real-time workloads.
Optimize GPU/CPU utilization and memory footprint for large models.
Build scalable inference pipelines for translation, ASR, and RAG.
• Audio & Video Processing Systems
Develop advanced audio transcription and 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.
• RAG & LLM-Based Systems
Architect multilingual Retrieval-Augmented Generation (RAG) pipelines.
Build vector databases and embedding models.
Implement document indexing, chunking, parsing, and hybrid retrieval search.
Integrate LLMs (Llama, Gemma, Qwen etc.) for chatbot and voice-bot systems.
• Infrastructure & Server Management
Manage AI/ML servers on AWS & GCP (GPU VM provisioning, optimization).
Reduce infra cost by optimizing GPU usage, scheduling, and server consolidation.
Implement auto-restart, monitoring, logging, and fail-safe mechanisms for all AI services.
Deploy high-availability APIs for translation, transliteration, ASR, OCR, and chatbots.
Familiarity with cloud-based GPU environments and troubleshooting (NVIDIA drivers).
• Cross-Functional Ownership
Work with Sales, Ops, Tech teams to troubleshoot, support clients, and deliver large projects.
Maintain detailed documentation for product flows, APIs, model deployments.
Handle urgent escalations, server crashes, and mission-critical deployments.
Create internal tools and FAQs to reduce dependency on the AI team.

Required Skills & Experience
Technical Skills
Strong background in NLP, Speech, Deep Learning, and Generative AI.
Experience: 4-5 years in production ML/NLP systems

Hands-on experience with:
Python, PyTorch, TensorFlow
Speech to text and Text to speech models, open source LLMs, Transformer architectures
CTranslate2, Faster-Whisper, ONNX Runtime
LLM inference frameworks like, vLLM, Sglang, LLM quantization techniques
Vector DBs (FAISS, Pinecone)
Docker, FastAPI, Linux systems
AWS/GCP GPU Infrastructure
Expertise in multilingual NLP, especially Indian languages.
Experience creating datasets and training models from scratch.

Bonus Skills
Experience with, WebRTC or real-time streaming protocols
Frontend basics for AI demo dashboards (Streamlit/Gradio).
Knowledge of TTS, voice pipelines, barge-in systems, or telephony APIs.
Experience with NVIDIA NeMo or similar speech frameworks
Soft Skills
Strong ownership and accountability.
Excellent communication and documentation clarity.
Ability to independently research, prototype, and deploy new systems.
Strong prioritization and deadline management.
Ability to handle high-pressure production issues.