
Cognitica AI is a leading provider of innovative AI-based industrial safety products and solutions designed to prevent workplace injuries and save lives. Their product suite includes AI vision systems like Falco F1 AI, Falco P1 AI, Falco X1 AI, and Infy X1 AI, which provide 360-degree safety zones, continuous human presence detection, PPE compliance monitoring, and quality control inspection. These solutions leverage deep neural networks to deliver human vision-like vigilance in industrial and warehouse environments, enhancing safety and productivity. Cognitica AI's technology is proven with multi-year successful deployments in industrial plants, positioning them as a key player in AI-driven industrial safety.

Cognitica AI is a leading provider of innovative AI-based industrial safety products and solutions designed to prevent workplace injuries and save lives. Their product suite includes AI vision systems like Falco F1 AI, Falco P1 AI, Falco X1 AI, and Infy X1 AI, which provide 360-degree safety zones, continuous human presence detection, PPE compliance monitoring, and quality control inspection. These solutions leverage deep neural networks to deliver human vision-like vigilance in industrial and warehouse environments, enhancing safety and productivity. Cognitica AI's technology is proven with multi-year successful deployments in industrial plants, positioning them as a key player in AI-driven industrial safety.
Cognitica AI hiring - AI/ML Engineer
Company: Cognitica AI Private Limited
Experience: 3 to 6 Yrs
Education: Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or a related field.
Immediate or 30 days notice period candidates are highly prepared.
Location: Coimbatore
Job Description: ML/AI Engineer (Computer Vision & LLM)
We are seeking a highly skilled and motivated to join our AI team. As a key member, you will play a pivotal role in the development and implementation of cutting-edge solutions across computer vision and large language models (LLMs) for diverse applications.
Your expertise will drive innovation in image/video analysis, object detection, facial recognition, and LLM-based solutions like Vector RAG, CoT, and ReAct (Agentic) workflows.
Responsibilities
Computer Vision:
* Develop and implement computer vision algorithms and models to address complex challenges in image and video analysis.
* Utilize libraries like OpenCV, Dlib, and frameworks like TensorFlow, Keras, and PyTorch.
Implement state-of-the-art algorithms, including YOLO (version 5+), Faster R-CNN, CNN, SORT, Deep-SORT, and Mask R-CNN.
* Work on facial feature extraction and optimization for real-world applications.
Large Language Models (LLMs):
* Design and implement Vector RAG pipelines, focusing on Chain-of-Thought (CoT) and ReAct (Agentic) methods.
* Utilize and fine-tune LLMs like OpenAI GPT, Gemini, Claude, or similar models.
* Develop and test prompt engineering strategies to maximize model performance.
* Work with libraries such as Transformers, Hugging Face, and LangChain to build scalable solutions.
* Implement chunking techniques, manage embeddings, and ensure seamless integration with vector databases.
General AI/ML Responsibilities:
* Collaborate with cross-functional teams to define requirements and deliver robust solutions.
* Optimize and deploy AI models on cloud platforms like AWS, GCP, or Azure.
Requirements
Core Skills:
* Expertise in computer vision algorithms and libraries such as OpenCV, Dlib, and TensorFlow/Keras/PyTorch.
* Proficiency with algorithms like YOLO (v5+), Faster R-CNN, Mask R-CNN, and DeepSORT.
* Hands-on experience with LLM models like OpenAI GPT, Claude, Gemini, or similar.
* Knowledge of fine-tuning, embeddings, and chunking techniques for large datasets.
* Familiarity with vector databases such as Pinecone, Milvus, or Weaviate.
* Strong skills in Python and related libraries (NumPy, Pandas, Matplotlib, Scikit-learn, Seaborn).
Preferred Skills:
* Experience with LangChain and Hugging Face Transformers.
* Familiarity with DevOps practices and CI/CD workflows for AI/ML deployments.
* Knowledge of optimization techniques for inference, including quantization and pruning.
* Exposure to Reinforcement Learning, edge computing, and GANs.