We are seeking an AI Engineer to join our dynamic team and contribute to the development and enhancement of our AI-driven platforms. The ideal candidate will possess deep technical expertise in machine learning and artificial intelligence, with a proven track record of developing scalable AI solutions.

Your role will involve everything from data analysis and model building to integration and deployment, ensuring our AI initiatives drive substantial business impact.

Responsibilities :

- Lead the development of end-to-end machine learning solutions including data extraction, model training, inference, and deployment.

- Build and optimize scalable AI applications using tools such as Python, TensorFlow, PyTorch, and transformer-based models (BERT, Llama, GPT-4).

- Implement multimodal systems including OCR, NLP, computer vision, and real-time conversational agents.

- Fine-tune LLMs using prompt engineering, custom datasets, and vector search (Pinecone, LangChain) to reduce hallucinations and boost model accuracy.

- Develop CI/CD pipelines for model versioning, automated deployment, and cost-aware infrastructure scaling.

- Construct and deploy cloud-based ML pipelines using Azure, and GCP (Lambda, S3, BigQuery, Cloud Functions).

- Integrate ML systems into full-stack applications (React, FastAPI), ensuring performance, security, and usability.

- Collaborate with cross-functional teams to understand business needs and translate them into data-driven solutions.

- Document model architecture, data flows, and deployment procedures for ongoing support and audit purposes.

Requirements and skills :

- Degree in Computer Science, Engineering, or related field.

- 3+ years of hands-on experience building and deploying machine learning systems.

- Experience with machine learning ops, LLMs, deep learning, OCR, NLP, and computer vision.

- Experience with tools and platforms including: TensorFlow, PyTorch, HuggingFace, FastAPI, React, Jenkins, Docker, Kubernetes.

- Strong SQL and data engineering experience with cloud platforms (Azure/GCP).

- Experience with cloud-based infrastructure and infrastructure-as-code (Terraform preferred).

- Excellent problem-solving skills and ability to work independently on complex challenges.

- Exceptional communication skills, with the ability to clearly explain ML concepts to non-technical stakeholders.

Mandate:

- Working on Azure cloud is must.