Quinnox - Data Scientist - Artificial Intelligence/Machine Learning

Description :

About the Role :

We are looking for a highly skilled Data Scientist with strong expertise in AI/ML and Generative AI to design, develop, and deploy intelligent solutions across document processing, computer vision, and large language models (LLMs). The ideal candidate will work closely with cross-functional teams to build scalable AI services and production-ready ML systems.

Key Responsibilities :

- Design, develop, and deploy AI/ML models with a focus on LLMs, Computer Vision, OCR, and Deep Learning use cases.

- Build and optimize document intelligence pipelines using OCR frameworks such as AWS Textract, Azure Form Recognizer, Google Document AI, and Mistral OCR.

- Develop end-to-end AI services and APIs using Python, FastAPI, and/or Flask.

- Integrate LLMs with enterprise applications, leveraging platforms like Amazon Bedrock, OpenAI, and Hugging Face.

- Work with vector databases (Pinecone, FAISS, Weaviate) for semantic search, RAG (Retrieval Augmented Generation), and contextual AI solutions.

- Deploy and manage AI/ML solutions on cloud platforms (AWS, Azure, GCP) using native AI/ML services.

- Evaluate model performance using appropriate AI/ML evaluation metrics for :

1. LLM responses and hallucination detection

2. Classification and detection models

3. OCR accuracy, precision, recall, and confidence scoring

- Collaborate with product managers, engineers, and stakeholders to translate business requirements into scalable AI solutions.

- Stay updated with the latest advancements in Generative AI, LLMs, and ML best practices and apply them to real-world problems.

Required Skills & Qualifications :

- 4- 10 years of hands-on experience in Data Science, Machine Learning, or AI development.

- Strong expertise in Python and ML/DL frameworks such as PyTorch and/or TensorFlow.

- Proven experience with LLMs, Computer Vision, OCR, and Deep Learning.

- Hands-on experience with OCR frameworks :

1. AWS Textract

2. Azure Form Recognizer

3. Google Document AI

4. Mistral OCR

- Experience building REST APIs using FastAPI or Flask for AI services.

- Working knowledge of vector databases like Pinecone, FAISS, or Weaviate.

- Experience integrating LLMs using Bedrock, OpenAI APIs, or Hugging Face.

- Strong understanding of model evaluation metrics across LLMs, classification, detection, and OCR use cases.

- Experience working with cloud-based AI/ML services on AWS, Azure, or GCP.

Good to Have :

- Experience with RAG architectures and prompt engineering.

- Exposure to MLOps practices, CI/CD for ML, and model monitoring.

- Understanding of data security, privacy, and compliance in AI systems.

- Ability to optimize models for performance, scalability, and cost.

What We Offer :

- Opportunity to work on cutting-edge AI and Generative AI solutions.

- Exposure to large-scale, real-world AI deployments.

- Collaborative and innovation-driven work environment.

- Competitive compensation and growth opportunities.