33 Ai Implementation Jobs - Page 2

Hands on experience (current or earlier) in ML projects (Predictive modelling) - 5 +yrs. Trained on AIML from IIIT Hyderabad in 2018 and then started working on internal AIML project for Content Management Vertical. Implemented and deployed machine learning models for Euroclear and Selective insurance. Working on AIML projects for more than 5 years. Passionate about staying at the forefront of AI advancements and contributing to a culture of innovation and excellence. Experience in managing projects and team end to end 15 yrs. Joined Capgemini in 2008 as Lead consultant and worked as Project Manager / Technical Lead / SME / Architect and responsible for end to end project delivery till April...

You will be joining our global team as a KBS Testing (Key Business Service) Testing specialist to support the increasing focus on KBS application testing worldwide. Your role is pivotal in a comprehensive testing program aimed at reducing risks and enhancing overall resilience. In the Technology division, we harness innovation to establish connections and capabilities that drive our Firm, empowering our clients and colleagues to redefine markets and shape the future of our communities. You will be part of the RTEP Recovery Testing program which focuses on establishing testing frameworks and collaborating with technology stakeholders to conduct testing and exercise events to validate recovery...

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

1) Strategic Leadership,Innovation 2) Operations,Process Optimization 3) Safety, Compliance,Sustainability 4) Research & Development (R&D),Innovation 5) Sustainability & ESG Initiatives 6) Capital Projects & Expansion 7) Leadership & Team Development Required Candidate profile Leader driving AI automation, Industry 4.0 & sustainability Ensure carbon neutrality, efficiency, safety& team growth Skilled in equipment design, integration, collaborate with marketing, finance, HR

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.