AI Engineer - Senior

Key Responsibilities1. AI Model Development & Training

• Build, train, and fine-tune models across:
• Multilingual NMT & Adaptive Translation models
• Transliteration models for Indian languages
• ASR systems (Whisper, NVIDIA NeMo, Indic-ASR)
• TTS models
• LLMs & embedding models for RAG
• Create and manage large multilingual datasets (20+ Indian languages).
• Perform dataset preprocessing, augmentation, and large-scale training.
• Benchmark models using BLEU, chrf++, WER, CER, and custom metrics.
• Convert and optimize models using CTranslate2, Faster-Whisper, ONNX, INT4/INT8 quantization, etc.

2. Model Optimization for Production

• Reduce model size using pruning and quantization.
• Optimize inference for real-time workloads.
• Improve GPU/CPU utilization and memory efficiency.
• Build scalable inference pipelines for translation, ASR, OCR, and RAG systems.

3. Audio & Video Processing Systems

• Develop advanced audio transcription & translation pipelines.
• Implement real-time Indic language STT systems.
• Create subtitle extraction and SRT translation workflows.
• Integrate diarization, language detection, summarization, and cross-lingual translation components.

4. RAG & LLM-Based Systems

• Architect multilingual RAG pipelines.
• Build vector databases and embedding systems.
• Implement document parsing, indexing, chunking, and hybrid retrieval.
• Integrate LLMs (Llama, Gemma, Qwen, etc.) for chatbot/voice-bot solutions.

5. Infrastructure & Server Management

• Manage AI/ML infrastructure on AWS & GCP (GPU provisioning, tuning).
• Optimize GPU usage, reduce infra cost, and manage server scheduling.
• Implement monitoring, auto-restart, logging, and fail-safe systems.
• Deploy highly available APIs for translation, ASR, OCR, and chatbot services.
• Troubleshoot cloud GPU environments (NVIDIA drivers, CUDA issues).

6. Cross-Functional Collaboration

• Work with Sales, Ops, and Tech teams to support enterprise and government clients.
• Handle escalations, server outages, and critical deployments.
• Maintain detailed documentation for APIs, model flows, and deployment processes.
• Build internal tools to streamline workflows and reduce team dependencies.

Required Skills & ExperienceTechnical Skills

• Strong foundation in NLP, Speech Processing, Deep Learning, and Generative AI.
• 4–5 years of hands-on experience with production-grade ML/NLP systems.
• Proficiency in:
• Python, PyTorch, TensorFlow
• ASR, TTS, LLMs, and Transformer-based architectures
• CTranslate2, Faster-Whisper, ONNX Runtime
• LLM inference frameworks: vLLM, SGLang
• Quantization techniques (AWQ, INT4/INT8)
• Vector DBs: FAISS, Pinecone
• Docker, FastAPI, Linux
• AWS/GCP GPU Infrastructure
• Expertise in Indian language NLP and multilingual model building.
• Experience creating datasets and training models from scratch.

Bonus Skills

• Knowledge of WebRTC or real-time streaming protocols.
• Experience with Streamlit/Gradio for AI demos.
• Familiarity with TTS, voice pipelines, barge-in systems, telephony APIs.
• Experience with NVIDIA NeMo or similar speech frameworks.

Job Types: Full-time, Permanent

Pay: ₹1,200,000.00 - ₹1,500,000.00 per year

Benefits:

• Paid time off

Application Question(s):

• Notice Period

Experience:

• total work: 4 years (Preferred)
• AI: 4 years (Preferred)
• NLP : 4 years (Preferred)

Work Location: In person