AI /Artificial Intelligence Engineer- Gurgaon (Haryana)

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. Required Software Engineering Skills: - 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. Soft Skills: - 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. Key Responsibilities: - 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 transparent 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. Qualifications: - Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field. - 2-9 years of experience in developing and deploying AI applications. - Proven track record of delivering scalable AI solutions in an enterprise setting. .