AI ML Engineer

Primary Responsibilities:

• Technically lead cross-location teams of 5-6 members to drive effective delivery
• Deliver innovative solutions that resolve application issues efficiently
• Contribute to architecture discussions and design reviews that strengthen solution quality
• Build trusted engagement with stakeholders and leadership to align delivery outcomes
• Serve as the SME for the assigned functional/application area, enabling informed decisions
• Optimize program logic to improve system performance and reliability
• Assess feasibility for new or expanded systems to support scalable growth
• Provide end-to-end application ownership to ensure accountable and consistent delivery
• Design, build, and deploy scalable AI-powered solutions that create measurable value
• Apply SDLC and Agile expertise to support structured, high-quality delivery
• Communicate clearly and effectively to influence alignment and execution
• Demonstrate flexibility to support business-critical needs and timelines
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelors or Master''s degree in Computer science , data science , statistics or a related field (Minimum 16 years of formal education, Correspondence courses are not relevant)
• Experience to build and deploy web and AI/ML applications using Python, NumPy, Pandas, PyTorch, TensorFlow, and FastAPI
• Experience to use GenAI frameworks: LangChain, LangGraph, and Pydantic
• Experience to perform exploratory data analysis using standard EDA techniques
• Experience to evaluate models, use cases, errors, and performance metrics
• Experience to apply deep learning algorithms: ANN, CNN, RNN, LSTM, VAE, and GPT
• Experience to implement CI/CD with Jenkins/GitHub, Kubernetes, Terraform, and Azure
• Experience to design agentic architectures using design patterns and MCPs
• Experience to create effective prompts and work with SQL and NoSQL databases

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