Design, develop, and implement machine learning models for data analysis, predictive analytics, and AI-driven solutions.
Utilize supervised and unsupervised learning techniques, including Generative AI (GenAI) and Large Language Models (LLMs), to build and optimize advanced ML systems.
Perform data analysis, preprocessing, and feature engineering to support model training and integration.
Collaborate with cross-functional teams to integrate ML solutions with source systems and ensure smooth data flow.
Continuously improve models through iterative testing, tuning, and performance optimization.
Contribute to the development of ML workflows, pipelines, and model deployment strategies.
Stay updated on industry trends and emerging technologies in machine learning and AI.
Must-Haves
Proficiency in Python programming, with strong knowledge of relevant libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.
Strong understanding of Linux operating systems and related tools for efficient development and deployment.
Extensive knowledge and hands-on experience with supervised and unsupervised learning, as well as Generative AI (GenAI) and Large Language Models (LLMs).
Experience in data analysis and building advanced machine learning models.
Expertise in integrating ML solutions with source systems to ensure seamless data handling.
Familiarity with version control systems (e.g., Git) and collaboration tools (e.g., Jira, Confluence).
Nice to Have
Experience with cloud-based ML platforms (AWS, GCP, Azure).
Knowledge of MLOps principles for model deployment and lifecycle management.