S&P Global is hiring for the role of Associate -AI Engineer!

Responsibilities of the Candidate:

• Develop and implement machine learning models: Design, build, and train traditional machine learning models (e.g., regression, classification, clustering) for tasks such as risk assessment, fraud detection, trade prediction, and operational efficiency.
• Explore and apply generative AI techniques: Research, experiment with, and implement generative AI models (e.g., transformers, large language models) for applications like data augmentation, synthetic data generation, anomaly detection, and natural language processing in financial contexts.
• Collaborate on AI solutions: Work closely with experienced AI engineers, data scientists, and software developers to integrate AI models into Osttra's existing systems and build new AI-powered applications.
• Contribute to software development: Participate in the full software development lifecycle, including design, coding, testing, and deployment, adhering to best practices and industry standards.
• Analyze and interpret data: Analyze large datasets, identify patterns and trends, and derive insights to inform model development and business decisions.
• Stay current with AI advancements: Continuously learn and keep abreast of the latest research and trends in both traditional machine learning and generative AI.
• Communicate effectively: Clearly communicate technical concepts and findings to both technical and non-technical audiences.

Requirements:

• Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong understanding of fundamental AI/ML concepts (e.g., supervised/unsupervised learning, deep learning, natural language processing).
• Experience with Python and relevant AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Familiarity with generative AI models and frameworks (e.g., transformers, GPT).
• Proficiency in software engineering principles and practices.
• Knowledge of data structures, algorithms, and databases.
• Excellent analytical and problem-solving skills.
• Strong communication and collaboration skills.
• Ability to work independently and as part of a team