Description

You will design and manage data systems and machine learning solutions using large language models and advanced data architecture.

Responsibilities

• Develop and manage data systems using enterprise data management practices.
• Implement generative AI solutions utilizing LLMs, VLMs, and prompt engineering.
• Build and integrate APIs to support model functionality and data flow.
• Deploy machine learning models into production environments using Docker, Kubernetes, or GCP.
• Execute data preprocessing, feature engineering, and large-scale data handling.

Required Skills

• 6 to 10 years of professional experience in machine learning or data science roles.
• Strong programming proficiency in Python.
• Deep expertise in Large Language Models (LLMs) and Vector Databases.
• Hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
• Proven knowledge of supervised, unsupervised, and reinforcement learning algorithms.
• Experience with data manipulation libraries including Pandas and NumPy.
• Practical experience in Data Architecture and Enterprise Data Management.
• Proficiency in model deployment via Docker, Kubernetes, or cloud services.
• Familiarity with advanced techniques such as Tree of Thought.

Key Skills

Education

Any Graduate