Description

*About the Role:*
We are seeking an experienced AI Subject Matter Expert (SME) to lead the strategy, design, and implementation of Artificial Intelligence solutions across our organization. The ideal candidate will have deep technical expertise in AI technologies, machine learning, data analytics, and their 
application to solve complex business problems. 
Key Responsibilities:
Act as the technical authority and go-to expert for AI strategy, architecture, and implementation.
Design and develop advanced machine learning models, deep learning algorithms, and AI frameworks tailored to business needs.
Collaborate with cross-functional teams (Data Engineers, Data Scientists, Business Analysts, and IT) to define and deliver AI-driven solutions.
Evaluate emerging AI technologies, tools, and frameworks; recommend best practices.
Provide subject matter expertise in areas such as Natural Language Processing (NLP), Computer Vision, Predictive Analytics, Reinforcement Learning, etc.
Define AI solution architecture .
Deliver technical workshops and training to upskill internal teams on AI concepts and tools.
Participate in strategic planning and advise senior leadership on AI trends and opportunities.
Required Qualifications:
Bachelor's or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
10+ years of experience in AI, machine learning, or advanced analytics roles.
Strong programming skills in Python, R, Java, or similar languages.
Hands-on experience with popular ML/DL frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, etc.
Expertise in data pre-processing, feature engineering, model building, hyperparameter tuning, and model evaluation.
Solid understanding of cloud platforms (AWS, Azure, GCP) and AI services.
Strong analytical, problem-solving, and decision-making skills.
Excellent communication skills to explain complex concepts to non-technical stakeholders.
Experience with big data technologies (Hadoop, Spark) is a plus.
Knowledge of deploying AI models into production environments using tools like Docker, Kubernetes, MLflow, etc.
Experience in implementing AI solutions in industries such as finance, healthcare, manufacturing, or retail.
Knowledge of AI ethics, data privacy regulations, and responsible AI principles.
Certification in AI/ML technologies (Google Professional ML Engineer, Microsoft Azure AI Engineer, etc.)

Key Skills

Education

Any Graduate