AI-ML SUPPORT ROLE - AI-ML ASSURANCE New Delhi | NA Posted On: 21-11-24 Max notice : Maximum One month/ immediate joiners
Experience: 4-5 years
Location: Bangalore only
**Candidate has to work on the Hardware at Bangaluru electronic city office
CTC: Upto 23 Lakhs
Key Responsibilities:
Design, develop, and optimize deep learning models for various applications, including NLP, computer vision, and deep leaning learning. Develop, test, and deploy scalable deep learning solutions using PyTorch and PyCUDA for GPU-accelerated computing. Implement efficient tokenization methods to enhance the performance of Language models. Collaborate with data scientists, software engineers, and product teams to integrate deep learning models into production systems. Analyze and interpret model performance and fine-tune algorithms to improve accuracy and efficiency. Stay updated with the latest research and advancements in deep learning technologies. Required Skills and Experience:
*Must have work experience in Nvidea Jetson Series **
Strong experience in developing deep learning algorithms for real-world applications. Excellent proficiency in Python development , with an ability to write clean, efficient, and well-documented code. Hands-on experience with PyTorch for building and training deep learning models. Solid understanding of tokenization techniques , especially in the context of NLP. Proficiency with GPU programming and optimization using PyCUDA or similar tools. Experience with debugging, profiling, and optimizing deep learning models for performance. Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. Preferred Qualifications:
Experience with other deep learning frameworks such as TensorFlow. Familiarity with distributed training techniques. Knowledge of model deployment frameworks like TensorRT or ONNX. Employment Type: Full Time, Permanent
Role Category: Quality Assurance and Testing
Education
UG: Any Graduate
PG: Any Postgraduate
Python PHP TensorFlow PyTorch Computer Vision Deep Learning Scala Tokenization Quality Assurance