Job Title : AI Engineer
Location : Kolkata, WB, India
Technical Expertise :
- Deep expertise in Natural Language Processing (NLP), including transformers, BERT, GPT, named entity recognition, and more.
- Strong background in Computer Vision, including CNNs, object detection, image segmentation, GANs, etc.
- Advanced proficiency in Python and AI-related libraries such as TensorFlow, PyTorch, and Keras.
- Experience designing and implementing scalable AI architectures and deploying AI models to production environments.
- Familiarity with cloud platforms (AWS, Google Cloud, Azure) and tools for AI deployment (e.g., Docker, Kubernetes).
- Strong knowledge of machine learning algorithms, data structures, and optimization techniques.
Key Responsibilities:
- Architect AI Solutions: Lead the design and architecture of end-to-end AI systems, especially in NLP and Computer Vision.
- Model Design & Optimization: Guide the design, development, and optimization of advanced deep learning models using frameworks like TensorFlow, PyTorch, and Keras for various applications.
- Research and Innovation: Conduct in-depth research to identify and implement the latest AI techniques and architectures for NLP (e.g., transformer models, BERT, GPT) and computer vision (e.g., CNNs, GANs, object detection).
- Scalable Systems: Architect scalable AI systems capable of handling large datasets and operating in real-time or near real-time environments.
- Collaboration: Work closely with product managers, engineers, and data scientists to seamlessly integrate AI solutions into production systems.
- Mentorship: Provide technical leadership, mentorship, and guidance to AI teams, ensuring the delivery of high-quality code, architecture, and model performance.
- Deployment & Maintenance: Oversee the deployment of AI models into production environments, ensuring they are optimized for efficiency, scalability, and long-term maintainability.
- Continuous Improvement: Stay updated with industry trends, continuously improving AI capabilities through experimentation with new techniques, algorithms, and tools.
Preferred Qualifications:
• Expertise in reinforcement learning or other advanced AI techniques.
• Experience with big data frameworks such as Hadoop and Spark.
• Familiarity with AI model interpretability and explainability techniques.
• Knowledge of containerization and deployment frameworks (Docker, Kubernetes, etc.).
• Proven track record of leading large-scale AI projects from concept to production.
Employment Type: Full Time, Permanent
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