We are looking for an experienced engineer to join our team who has expertise in Docker containerization, MLOps, PyTorch/TensorFlow/TensorRT frameworks, NVIDIA CUDA, NLP, and programming languages such as Python and C++.
The successfucandidate wilbe responsible for designing, developing, and implementing machine learning models in a production environment.
Responsibilities:
Design and develop Docker containerized applications for machine learning models.
Build and maintain scalable MLOps infrastructure.
Develop and optimize machine learning models using PyTorch, TensorFlow, and TensorRT.
Work with NLP models for text classification, sentiment analysis, and entity recognition.
Collaborate with cross-functionateams including data scientists, software engineers, and DevOps to integrate Mmodels into production environments.
Provide technicaguidance and support to the team members.
Stay up-to-date with the latest technologies and trends in machine learning, NLP, Docker, and MLOps.
Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
2+ years of experience in designing and developing Docker containers for production environments.
2+ years of experience in MLOps and building scalable machine learning infrastructure.
Proficient in PyTorch, TensorFlow, and TensorRT frameworks and optimizing machine learning models using GPU acceleration with NVIDIA CUDA.
Strong background in NLP and experience with popular NLP libraries such as NLTK, spaCy, Gensim, Nvidia Nemo, transformers-based models.