AI Technical Specialist

Dear Candidates,

Greetings from TCS!!!!

TCS is looking for AI Technical Specialist

Experience: 6-8 years

Location: Hyderabad / Mumbai / Bangalore

Must have skills:

• Design end-to-end AI solution architectures that are scalable, secure, and align with business objectives and technical requirements.
• Create detailed architectural plans for AI systems, including data pipelines, model deployment strategies, and integration with existing IT infrastructure.
• Collaborating with cross-functional teams of data scientists, software developers, and business stakeholders to understand requirements and translate them into AI solutions.
• Evaluate and select the most suitable tools, platforms, and technologies for AI development, considering factors like scalability, cost, and compatibility.
• Oversee the development and training of machine learning models, ensuring they meet the desired performance metrics. Good to have hands-on experience on any AI platform.
• Analyze large datasets to extract meaningful insights and patterns that can inform AI model development.
• Oversee and ensure the integration of AI solutions with existing enterprise systems, databases, infrastructure and alignment with CI/CD pipelines.
• Optimizing and fine-tuning existing AI models to enhance their accuracy, efficiency, and performance.
• Deploying AI solutions into production environments and ensuring their integration with existing systems. Good to have hands-on experience on any API integration platform.
• Monitoring and evaluating the performance of AI systems, adjusting as necessary to improve outcomes.
• Manage potential risks and implement AI technologies, applications, and infrastructure in keeping with ethical policies.

Good to have skills:

• Design end-to-end AI solution architectures that are scalable, secure, and align with business objectives and technical requirements.
• Create detailed architectural plans for AI systems, including data pipelines, model deployment strategies, and integration with existing IT infrastructure.
• Collaborating with cross-functional teams of data scientists, software developers, and business stakeholders to understand requirements and translate them into AI solutions.
• Evaluate and select the most suitable tools, platforms, and technologies for AI development, considering factors like scalability, cost, and compatibility.
• Oversee the development and training of machine learning models, ensuring they meet the desired performance metrics. Good to have hands-on experience on any AI platform.
• Analyze large datasets to extract meaningful insights and patterns that can inform AI model development.
• Oversee and ensure the integration of AI solutions with existing enterprise systems, databases, infrastructure and alignment with CI/CD pipelines.
• Optimizing and fine-tuning existing AI models to enhance their accuracy, efficiency, and performance.
• Deploying AI solutions into production environments and ensuring their integration with existing systems. Good to have hands-on experience on any API integration platform.
• Monitoring and evaluating the performance of AI systems, adjusting as necessary to improve outcomes.
• Manage potential risks and implement AI technologies, applications, and infrastructure in keeping with ethical policies.

Roles and responsibilities:

• Design end-to-end AI solution architectures that are scalable, secure, and align with business objectives and technical requirements.
• Create detailed architectural plans for AI systems, including data pipelines, model deployment strategies, and integration with existing IT infrastructure.
• Collaborating with cross-functional teams of data scientists, software developers, and business stakeholders to understand requirements and translate them into AI solutions.
• Evaluate and select the most suitable tools, platforms, and technologies for AI development, considering factors like scalability, cost, and compatibility.
• Oversee the development and training of machine learning models, ensuring they meet the desired performance metrics. Good to have hands-on experience on any AI platform.
• Analyze large datasets to extract meaningful insights and patterns that can inform AI model development.
• Oversee and ensure the integration of AI solutions with existing enterprise systems, databases, infrastructure and alignment with CI/CD pipelines.
• Optimizing and fine-tuning existing AI models to enhance their accuracy, efficiency, and performance.
• Plan and Drive enterprise-wide AI literacy and capability development programs, manage organizational change, and foster a culture of continuous learning and innovation.
• Develop actionable roadmaps, oversee the development and deployment of AI models, and ensure successful integration with existing systems and workflows.
• Deploying AI solutions into production environments and ensuring their integration with existing systems. Good to have hands-on experience on any API integration platform.
• Monitoring and evaluating the performance of AI systems, adjusting as necessary to improve outcomes.
• Manage potential risks and implement AI technologies, applications, and infrastructure in keeping with ethical policies