Company:Global Technology organization

Key Skills: Machine Learning, Python, Generative AI, Gen AI, AI/ML, LLM, ML Engineering, Spark, PySpark, SparkSQL, Apache Spark, Azure, AWS

Roles & Responsibilities:

Develop and deploy agentic AI workflows to support business processes within the private equity value chain.
Design, build, and optimize machine learning models and Generative AI solutions for enterprise applications.
Implement advanced practices in context engineering and evaluation frameworks for AI agents.
Research, train, fine-tune, and evaluate AI models to optimize performance and achieve defined objectives.
Build scalable web services and APIs to support model inferencing and AI-driven applications.
Develop and manage AI-ready data pipelines integrating structured and unstructured data sources.
Work with tools, functions, and Model Context Protocol (MCP) services to support AI workflows.
Ensure best practices in data quality, governance, security, and compliance.
Collaborate with data scientists, engineers, and stakeholders to support modeling and application needs.
Monitor and optimize performance of data and model pipelines, troubleshooting issues in real time.
Contribute to improving system reliability, scalability, and efficiency in AI-powered platforms.

Experience Required:

5 - 8 years of experience in machine learning, AI/ML engineering, or data engineering roles.
Strong programming experience in Python for machine learning and data processing.
Hands-on experience with Generative AI, LLM-based applications, and AI model deployment.
Experience working with big data technologies such as Apache Spark, PySpark, or SparkSQL.
Familiarity with cloud platforms such as Azure or AWS.
Experience building scalable data pipelines and AI inference services.
Strong understanding of machine learning lifecycle, model evaluation, and optimization techniques.
Experience working with cross-functional teams in data-driven environments.

Education: Any Graduation

Senior Machine Learning Engineer_96630