Description

Transform complex datasets into actionable insights using statistical techniques and machine learning models.

This role is on-site.

Responsibilities

• Analyze large datasets to identify patterns, trends, and insights.
• Develop, test, and implement machine learning and generative AI models, including LLMs and text-to-image models.
• Partner with data engineering teams to define requirements and optimize data pipelines.
• Conduct hypothesis testing, A/B testing, and regression analysis to validate business assumptions.
• Collaborate with engineering teams to deploy models into production and monitor performance.

Required Skills

• 5+ years of experience developing and training AI/ML models.
• Proficiency in Python and SQL.
• Experience with R or other statistical/mathematical software.
• Knowledge of machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
• Experience with generative AI models such as GPT, LLaMA, Gemini, and DALL-E.
• Practical experience with cloud infrastructure including Azure, GCP, or AWS.
• Strong understanding of deep learning, natural language processing, and computer vision.
• Bachelor's or master's degree in computer science, engineering, or a related field.

Preferred Skills

• Experience with version control systems like Git.
• Familiarity with cloud-based ML model deployment using Azure ML or AWS SageMaker.

Key Skills

Education

Bachelor's or master's degree in computer science, Data Science