Key Responsibilities:
Collaborate with business stakeholders to understand strategic objectives, pain points, and opportunities where AI/ML can provide value.
Define end-to-end AI architectures, including data pipelines, model training and deployment, inferencing, and integration with enterprise systems.
Lead the evaluation, selection, and implementation of AI frameworks, tools, and platforms (e.g., TensorFlow, PyTorch, Azure ML, AWS SageMaker).
Translate business problems into well-defined machine learning and AI problem statements and recommend appropriate models or approaches.
Ensure AI solutions are scalable, explainable, ethical, and aligned with data governance and compliance standards.
Work with data scientists, data engineers, and product teams to deliver AI-powered applications, APIs, or platforms.
Guide teams in model optimization, A/B testing, monitoring, and continuous improvement.
Stay current on AI/ML research and trends to recommend emerging capabilities aligned with business needs.
Prepare business cases, ROI estimates, and solution blueprints to support AI-driven initiatives.
Build reference architectures, reusable components, and knowledge assets to scale AI adoption.
Required Skills & Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field (Ph.D. preferred).
13+ years in technology with at least 4+ years in AI/ML solution architecture.
Deep understanding of machine learning, deep learning, NLP, computer vision, and generative AI concepts.
Strong experience in designing and deploying AI solutions in cloud environments (Azure, AWS, or Google Cloud Platform).
Hands-on experience with Python, R, or Scala, and ML libraries like scikit-learn, Keras, Hugging Face, etc.
Strong grasp of data engineering principles, including data preparation, feature engineering, and model deployment.
Ability to communicate technical concepts clearly to business stakeholders and convert requirements into actionable designs.
Familiarity with MLOps practices, model lifecycle management, and monitoring tools.
Excellent analytical, presentation, and stakeholder engagement skills.
AI – Preferably GenAI (experience in few Vector DBs)
Python, PySpark
AI services in any of the cloud environments.
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