Machine Learning Engineer

Found in: beBee jobs NG - 1 week ago

Abuja, FCT, Nigeria Uniccon Group Full time
  • 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.

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