Gen AI Lead

2 days ago


Kollam, India EXL Full time

Locations: Bangalore/ Gurgaon Role and Responsibilities: - SME for clients: Serve as the primary point of contact for clients in Gen AI needs, including senior executives, to understand their needs and deliver tailored generative AI solutions. - Project Leadership: Lead multiple generative AI projects, ensuring timely delivery and high-quality outcomes. Define project deliverables, timelines, and methodologies. - Team Management: Manage and mentor a team of AI specialists, fostering a collaborative and innovative environment. - Solution Design: Architect and implement advanced generative AI models, including GANs, VAEs, and transformer-based models, to solve complex business problems. - Thought Leadership: Provide strategic insights and thought leadership in generative AI, driving innovation and best practices within the organization. - Technical Expertise: Stay abreast of the latest advancements in generative AI and machine learning, integrating cutting-edge technologies into projects. Qualifications: - Educational Background: Master's or PhD in computer science, engineering, mathematics, or related fields from top-tier institutions. - Experience: 8+ years of experience in AI and machine learning, with a focus on generative AI, deep learning, and NLP. Proven track record in delivering generative AI projects. - Technical Skills: Proficiency in Python, TensorFlow, PyTorch, Keras, and cloud platforms (AWS, Azure, GCP). Experience with large-scale data processing and model deployment. - Certifications: Relevant certifications in AI and machine learning, such as TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, or similar. (Preferred not mandatory) - Leadership: Demonstrable leadership ability, with experience managing and mentoring teams. - Problem-Solving: Superior problem-solving skills, with a track record of delivering innovative generative AI solutions. - Communication: Excellent communication and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders. - Industry Knowledge: Deep understanding of industry trends and challenges in generative AI and machine learning.


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