Manager – Generative AI Technical Lead
1 week ago
Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI
Inviting applications for the role ofManager – Generative AI Technical Lead
We are seeking an experienced Technical Architect with a strong background in Generative AI to lead the design, development, and deployment of AI-driven solutions. The ideal candidate will have deep expertise in AI/ML frameworks, a solid understanding of software engineering principles, and the ability to architect scalable AI solutions that drive business value.
Key Responsibilities:
Solution Design and Architecture:
Lead the design and architecture of generative AI solutions, ensuring they meet business requirements and technical specifications.
Collaborate with stakeholders to translate business needs into technical solutions, including data requirements, model selection, and deployment strategies.
Develop end-to-end AI pipelines, from data ingestion and preprocessing to model training and deployment.
Technical Leadership:
Provide technical guidance and mentorship to development teams on AI/ML best practices.
Stay updated with the latest advancements in generative AI and evaluate their potential impact on current and future projects.
Conduct code reviews and ensure the quality and performance of AI solutions.
AI Model Development:
Design, build, and optimize generative AI models using state-of-the-art techniques and frameworks.
Experiment with different architectures, hyperparameters, and datasets to achieve optimal model performance.
Ensure models are robust, scalable, and efficient in production environments.
Collaboration and Communication:
Work closely with data scientists, engineers, and product managers to align AI initiatives with business objectives.
Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner.
Collaborate with external partners and vendors to integrate third-party AI solutions where necessary.
Project Management:
Lead and manage AI projects from conception to deployment, ensuring timely delivery and alignment with business goals.
Develop project plans, timelines, and resource allocation to ensure successful project execution.
Monitor project progress and adjust plans as needed to meet changing requirements and constraints.
Qualifications:
Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. A Ph.D. in a relevant area is a plus.
Experience:
Relevant years of experience in software development, with focused on AI/ML.
Proven experience in designing and deploying generative AI models (e.g., GPT, GANs, VAEs) in production environments.
Hands-on experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, Keras, Hugging Face, etc.
Technical Skills:
Strong programming skills in Python or similar languages.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI/ML services.
Proficient in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
Expertise in deploying AI models using Microsoft Azure OpenAI, Google Cloud AI, and AWS AI services.
Experience with large language models (LLMs) such as GPT-3, GPT-4, and other transformer-based models.
Familiarity with MLOps tools and practices for continuous integration and deployment of AI models.
Understanding of software engineering principles, including version control, testing, and CI/CD.
Soft Skills:
Excellent problem-solving abilities and analytical thinking.
Strong communication and interpersonal skills.
Ability to work in a fast-paced, collaborative environment.
Preferred Qualifications:
Certifications in AI/ML or cloud platforms.
Experience with fine-tuning and deploying LLMs for specific applications.
Knowledge of data privacy and ethical considerations in AI.
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