Job Description

As AI Solution Consultant, understand the customer needs and propose AI and Gen AI empowered practical in-depth solutions for solving customerbusiness problems. As AI Practice Head, research industry evolution in AI and Gen AI areas to identify practical differentiating solutions for solving business problems through AI and Gen AI. As AI and Data Solution Architect, Define the architecture, Design the solutions and Implement Cloud Data, AI and Gen AI based solutions for customer programs. Inspire, mentor, and build strong Data Engineering and AI practice delivery team to deliver the complex Data, AI and Gen AI programs for various customers. Conduct architecture reviews, design workshops and code reviews to deliver the outcome by collaborating with AI Data Scientists and Cloud Engineers. Apply statistics, modeling, and machine learning to improve the efficiency of systems and relevance algorithms across our business application products. Requirements Bachelordegree or Masterdegree in Computer Science / AIML / Data Sciences. 12+ years of overall experience and hands-on experience with the design + implementation of Machine Learning models, Deep Learning models for solving business problems. Expertise in R, Python (NumPy, Scikit-learn + Pandas), TensorFlow, PyTorch or MLlib and LLM solutions. Expertise in Cloud Data engineering solution architecture, design and implementation by using GCP / Azure. Excellent problem-solving and analytical skills with the ability to translate business requirements into data science solutions. Good experience in building complex and scalable Machine Leaning solutions and practically using in production. Experience with scripting in SQL - extracting large data sets and design of ETL flows. Deep interest and aptitude in data, metrics, analysis, trends and applied knowledge of measurement, statistics and program evaluation. Capable of translating analysis results into business recommendations. Effective communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.