• Uniccon Group is looking for a skilled Machine Learning Engineer with a strong background in deep learning and large language models (LLMs), particularly with experience in deploying and managing models using MLOps best practices.
• The ideal candidate will have hands-on experience with Hugging Face Transformers, Docker, PyTorch, and Python, along with a deep understanding of Machine Learning and LLMs.
• This role offers the opportunity to work on exciting projects that push the boundaries of AI and drive innovation.

Responsibility

• Develop and deploy deep learning models, with a focus on large language models, using PyTorch and Hugging Face Transformers.
• Update and Utilize currently existing Deployment architecture for efficient and scalable deep learning Inferencing.
• Collaborate with cross-functional teams to understand project requirements and design scalable solutions that leverage LLMs.
• Implement MLOps best practices for model deployment, monitoring, and management, ensuring reliability and scalability.
• Optimize and fine-tune models for performance and efficiency, considering factors such as speed, accuracy, and resource utilization.
• Conduct research to stay updated on the latest advancements in deep learning, LLMs, and MLOps, and incorporate best practices into our workflows.
• Work closely with data engineers to ensure seamless integration of data pipelines with model deployment processes.
• Develop automated testing and evaluation frameworks to assess model performance and identify areas for improvement.

Qualification and Skills –

• Bachelor’s or master’s degree in computer science, Engineering, Mathematics, or a related field.
• Proven experience in developing and deploying deep learning models, with a focus on large language models.
• Strong proficiency in PyTorch,Mlflow, Docker, Kubernetes, Hugging Face Transformers, and Python. Experience with MLOps best practices and tools for model deployment and management.
• In-depth understanding of parallel programming and distributed deep learning training.
• Deep understanding of large language models and their applications across various domains.
• Solid understanding of machine learning concepts and algorithms. Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.