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Role Overview
We are seeking an AI Engineer with expertise in
Retrieval-Augmented Generation (RAG), Computer Vision, and Deep Learning to build intelligent, context-aware AI systems. The role involves developing scalable AI pipelines that combine
LLMs, retrieval systems, and vision models to solve real-world problems.
Key Responsibilities
- Design and develop RAG-based AI systems integrating LLMs with structured/unstructured data sources
- Build and optimize end-to-end AI pipelines for Computer Vision (detection, segmentation, classification)
- Develop context-aware AI applications combining NLP + vision-based insights
- Implement vector search, embeddings, and retrieval pipelines
- Deploy scalable models using AWS serverless architecture (Lambda, API Gateway, ECR, SageMaker)
- Optimize model inference performance and latency in production
- Automate data pipelines including preprocessing, pseudo-labeling, and augmentation
Required Skills
- Strong experience in RAG frameworks and LLM integration
- Hands-on with vector databases (FAISS, Pinecone, etc.) and embeddings
- Expertise in Deep Learning Computer Vision (PyTorch / TensorFlow)
- Experience with OpenCV, NumPy, Pandas
- Strong programming in Python
- Knowledge of AWS / MLOps / Docker / APIs
Preferred Skills
- Experience building multi-modal AI systems (Vision + NLP)
- Familiarity with LLM orchestration tools (LangChain, LlamaIndex, etc.)
- Exposure to GANs, synthetic data, or auto-annotation pipelines
- Experience in real-time inference systems and optimization
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
