Senior AI Engineer

We are looking for a Senior AI Engineer to drive innovation in Computer Vision, NLP, and Large Language Models (LLMs) by developing and optimizing cutting-edge AI solutions. The ideal candidate will have a deep understanding of traditional and modern AI techniques, strong research and development (R&D) experience, and the ability to translate complex AI concepts into production-ready systems.

• Design, train, and deploy advanced Computer Vision, NLP, and LLM models.


• Work with both traditional ML (e.g., SVMs, Decision Trees) and deep learning techniques (e.g., CNNs, Transformers, Attention Mechanisms)


• Work on LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines


• Improve context-aware AI through knowledge graph integrations and semantic metadata filtering


• Build efficient embeddings and vector search solutions using techniques like FAISS, ANN, and Approximate Nearest Neighbors


• Build custom object detection, tracking, and segmentation pipelines for real-world applications


• Stay updated on cutting-edge AI research and incorporate state-of-the-art techniques into production systems. Conduct experiments with foundation models, model fusion, and domain-specific fine-tuning


• Work with MLOps and AI deployment strategies using tools like Docker, Kubernetes, TensorRT, ONNX, and Hugging Face


• Optimize inference pipelines for low-latency and high-throughput applications

• Strong expertise in AI and ML algorithms with a solid understanding of statistics, probability, and optimization techniques.


• Deep understanding of model architectures such as CNNs, YOLO, BERT, GPT, Vision Transformers (ViTs), and Attention Mechanisms.


• Experience in training, fine-tuning, and deploying deep learning models for computer vision and NLP applications.


• Strong R&D experience in experimenting with AI models, evaluating performance, and improving model generalization.


• Hands-on experience with AI/ML frameworks like PyTorch, TensorFlow, Hugging Face, OpenCV, FastAPI, and LangChain.


• Knowledge of retrieval-based AI systems, including semantic search, vector databases (FAISS, Pinecone, Qdrant), and hybrid search techniques.


• Strong understanding of model fusion, multi-modal AI, and ensemble learning techniques.


• Minimum 3 years of experience in AI/ML development, with a track record of deploying real-world AI solutions.


• Proficiency in Python, with experience in Numpy, Pandas, Scikit-learn, and AI model debugging tools.


• Familiarity with AI infrastructure and cloud computing (AWS, GCP, or Azure).


• Strong problem-solving skills and the ability to work in a fast-paced, research-driven environment.

This role offers a hybrid work model, combining remote and on-site work, providing flexibility while maintaining team collaboration.