AI/ML Engineer

Sr. AI Engineer

We are looking for a skilled Sr. AI Engineer / Data Scientist with hands-on experience in OCR pipelines and Large Language Model (LLM) fine-tuning. The ideal candidate will work on developing, fine-tuning, and optimizing a vision-language model (VLM) to extract structured information from scanned documents. You will collaborate with data scientists and backend engineers to build an accurate, high-throughput, and production-ready AI pipeline.

Fine-tune and adapt multimodal LLMs (e.g., Qwen-VL, LLaVA, or similar) for domain-specific document understanding.

Design prompt templates and instruction sets to improve JSON-structured output quality.

Perform differentfine-tuning and incremental learning across multiple datasets to ensure generalization.

Implement evaluation metrics and validation datasets to track model accuracy and performance.

Optimize inference performance using quantization, LoRA adapters, and Ray Serve / vLLM / Unsloth frameworks.

Collaborate with backend teams to integrate the model into production pipelines.

Build monitoring tools to log model confidence, token usage, and inference latency

Required Skills & Experience:

• Strong Python programming skills with experience in PyTorch and Transformers (Hugging Face).
• Experience working with OCR tools such as PaddleOCR, Tesseract, or EasyOCR.
• Hands-on experience fine-tuning or serving LLMs / VLMs (e.g., Qwen, LLaVA, Mistral, or Vicuna).
• Knowledge of LoRA / QLoRA / PEFT adapters for efficient model training.
• Familiarity with JSON schema generation, prompt engineering, and structured data extraction.
• Experience using Unsloth, Ray Serve, or vLLM for large-scale inference.
• Comfortable working with Docker, CUDA, and NVIDIA GPUs for model deployment.
• Strong understanding of tokenization, attention mechanisms, and quantization (4-bit / 8-bit )

Nice to Have:

• Experience with the LLM model serving
• Exposure to CI/CD pipelines and Azure / AWS / GCP deployments.
• Familiarity with PDF parsing frameworks (e.g., Camelot, PyMuPDF).
• Prior work on document intelligence or AI-based invoice understanding systems.

Opportunity to work with cutting-edge Vision-Language AI models.

Hands-on involvement in production-grade OCR-LLM pipelines.

Competitive compensation and flexible work culture.

Collaborative environment focused on AI innovation in enterprise document automation