AI Lead

The ideal candidate will have a solid foundation in software engineering, AI/ML technologies, and software development processes. The Candidate will be responsible for guiding a team of 4-5 AI developers, ensuring the delivery of robust AI solutions while maintaining high standards in architecture, coding practices, and project execution.

Required AI/ML Skills:

• Generative AI (GenAI):
• Experience with Large Language Models (LLMs) like GPT, BERT, or LLaMA.
• Familiarity with fine-tuning LLMs and integrating them into enterprise applications and Databases.
• Knowledge of text generation, summarization, translation, and conversational AI.
• Traditional Machine Learning:
• Proficiency in ML techniques like supervised learning, unsupervised learning, and reinforcement learning.
• Hands-on experience with classification, regression, clustering, and time-series forecasting.
• AI Frameworks and Tools:
• Proficient in frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn, and Keras.
• Familiarity with ML pipelines using tools like MLflow, Kubeflow, or TensorFlow Extended (TFX).
• Deployment:
• Knowledge of containerization (Docker, Kubernetes) and serverless architectures for scalable AI solutions.
• Programming Languages:
• Strong proficiency in Python (preferred), Java, or Go for AI application development.
• Experience with API development frameworks such as FastAPI, Django, or Flask.
• Architectural Concepts:
• Deep understanding of microservices architecture, event-driven design, and RESTful APIs.
• Knowledge of distributed systems and high-performance computing.
• Communication and Presentation:
• Excellent verbal and written communication skills, with the ability to simplify complex technical concepts for diverse audiences.
• Strong presentation skills to effectively convey architectural designs and project updates to customers and stakeholders.
• Team Collaboration:
• Proven experience in leading and mentoring technical teams, fostering collaboration, and encouraging continuous learning.
• Ability to work effectively across cross-functional teams including data engineers, product managers, and QA engineers.
• Technical Leadership:
• Lead, mentor, and guide a team of AI developers.
• Ensure adherence to best practices in software engineering, AI model development, and deployment.
• Review and approve architectural designs, ensuring scalability, performance, and security.
• AI Application Development:
• Architect and design AI solutions that integrate both Generative AI (GenAI) and traditional Machine Learning (ML) models.
• Oversee the end-to-end development lifecycle of AI applications, from problem definition to deployment and maintenance.
• Optimize model performance, ensure model explainability, and address model drift issues.
• Architectural Oversight:
• Develop and present the big-picture architecture of AI applications, including data flow, model integration, and user interaction.
• Dive deep into individual components, such as data ingestion, feature engineering, model training, and API development.
• Ensure the AI solutions align with enterprise architectural standards and customer requirements.
• Customer Engagement:
• Act as the primary technical interface for customer meetings, providing clear explanations of the AI solutions architecture, design decisions, and project progress.
• Collaborate with stakeholders to understand business needs and translate them into technical requirements.
• Ensure proper documentation, including design documents, code reviews, and testing protocols.
• Monitor project timelines and deliverables, ensuring high-quality outcomes.
• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field.
• 6-9 years of experience in developing and deploying AI applications.
• Proven track record of delivering scalable AI solutions in an enterprise setting.