AI / ML Engineer

About the Role:

AI/ML Engineer

Key Responsibilities:

• Design, build, and deploy intelligent AI agents and automation tools that optimize internal workflows and reduce repetitive tasks
• Develop machine learning models and algorithms to support decision-making and improve operational efficiency
• Implement AI-driven solutions for use cases such as task automation, knowledge retrieval, data summarization, and intelligent reporting
• Research and experiment with various AI/ML approaches to identify the best-fit technologies for business problems
• Collaborate with cross-functional teams to identify pain points and deliver AI-based tools that support their functions
• Apply prompt engineering and fine-tuning techniques to maximize the value of large language models (LLMs)
• Develop systems that enable automated document generation, test case creation, ticketing, and other IT operations
• Ensure ethical, efficient, and scalable implementation of AI across internal tools and processes
• Maintain clear documentation of AI workflows, architecture, and operational procedures

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
• Proficiency in Python and strong experience in machine learning and deep learning frameworks
• Proven experience in developing AI-powered agents, automation systems, or productivity-enhancing tools
• Strong understanding of NLP, ML algorithms, LLMs, and AI-driven workflow automation
• Ability to work independently on research and prototyping of new AI capabilities
• Excellent problem-solving and communication skills
• Comfortable working in fast-paced and agile environments

Preferred Qualifications:

• Experience in designing multi-agent systems or autonomous workflow assistants
• Understanding of retrieval-based systems, semantic search, or document intelligence
• Familiarity with MLOps practices and scalable deployment of ML solutions
• Experience using AI to automate software development lifecycle tasks such as code review, documentation, and QA
• Background in building internal tooling for IT or engineering teams