Gen Ai Lead

4 weeks ago

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 Ph D 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, Tensor Flow, Py Torch, 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 Tensor Flow 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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