Your primary responsibility is to design, develop, and optimize large language models, NLP systems, frameworks, and tools for both front-end and back-end development.
Prototypes and do proof of concepts (PoC)In : LLM, NLP, DL(Deep Learning), ML (Machine Learning), object detection / classification , tracking , etc
Stay up to date with the latest advancements in LLM, NLP, deep learning, machine learning, and object detection algorithms, and proactively identify opportunities to leverage new technologies for improved solutions.
Technical Skills:
Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc
Familiarity with cloud platforms (eg Kubernetes, AWS, Azure, GCP) and related services is a plus.
Researchers and engineers to build state-of-the-art language models that can understand and generate human-like text.
Work with business users to translate functional requirements into data specifications Collaborate with data scientists and business users to transform domain know-how into functional requirements.
Hands-on experience with Jupiter Notebooks, Docker, Kubernetes, Airflow, Kubeflow, MLOps, and DataOps principles.
Data Analysis and Pre-processing: Collect and pre-process large-scale text corpora to train and fine-tune language models. Conduct data analysis to identify patterns, trends, and insights that can inform model development and improvement.
Language Model Development: Utilize off-the-shelf LLM services, such as Cloud Open AI, to integrate LLM capabilities into applications, and collaborate with the research team to design and develop state-of-the-art language models.
Model Training and Evaluation: Train and fine-tune language models using appropriate machine-learning frameworks and tools.
