Artificial Intelligence Engineer

Role Overview We are seeking an experienced AI Technical Lead to spearhead the development and deployment of cutting-edge AI solutions. The ideal candidate will possess a strong foundation in AI algorithms, hands-on expertise with machine learning and deep learning frameworks, and a forward-thinking approach to leveraging emerging AI technologies like AGENTIC AI, RAG, Graph Databases, and open-source LLMs. This role also involves guiding the team to deliver scalable, efficient, and impactful AI products aligned with the EdTech domain. Key Responsibilities - AI Model Development: - Design, train, and deploy AI models for diverse use cases, including: - Computer Vision: Image recognition, object detection, segmentation etc. - Natural Language Processing (NLP): Text classification, summarization, question-answering systems etc. - Generative AI: Fine-tuning and deploying open-source large language models (LLMs) and Private Models. - RAG (Retrieval-Augmented Generation): Implement AI systems combining retrieval with generative models. - Optimize AI models for performance, scalability, and accuracy using core algorithms (regression, KNN, SVM, etc.). - Open-Source LLM Development: - Develop and fine-tune open-source LLMs to cater to domain-specific needs. - Deploy open-source LLMs effectively in production environments, ensuring scalability and low latency. - Explore and implement open-source tools and frameworks like Hugging Face, LangChain, and Transformer libraries. - Integration & Architecture: - Integrate AI solutions with Vector/Graph db for advanced data relationships and queries. - Implement and manage MLOps/LLMOps pipelines for efficient deployment, monitoring, and scaling of AI models. - Leadership: - Mentor and guide junior engineers, fostering innovation and skill development. - Collaborate with cross-functional teams, including product management, data engineering, and software development, to align AI strategies with business goals. - Infrastructure: - Leverage cloud AI platforms (AWS SageMaker, Google Vertex AI, Azure AI) for scalable solutions. - Adopt open-source frameworks and tools (e.g., TensorFlow, PyTorch, Hugging Face) for experimentation and development. - Best Practices: - Establish robust practices for coding, testing, and documenting AI solutions. - Stay at the forefront of AI research and emerging trends like AGENTIC AI, RAG, and open-source LLM development. Requirements Experience - 4+ years of experience in AI/ML. - Proven expertise in designing and deploying AI solutions in production environments. Technical Skills - Strong proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn). - Hands-on experience with tools like Hugging Face, OpenAI API, and Google AI tools. - In-depth understanding of core ML algorithms (regression, KNN, clustering, etc.) and deep learning models. - Familiarity with open-source LLM development and deployment - Experience with RAG architectures, Graph Databases, and LLMOps practices. - Expertise in CI/CD pipelines, containerization (Docker, Kubernetes), and cloud AI platforms (AWS, Google Cloud, Azure). Domain Knowledge - Familiarity with EdTech standards (LTI, xAPI, QTI) and adaptive learning systems is a strong plus. Soft Skills - Exceptional leadership and team mentoring abilities. - Strong problem-solving skills and excellent communication for technical and non-technical stakeholders. Education - Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields. Why Join Us - Drive AI initiatives shaping the future of education technology. - Work in a collaborative, innovation-focused environment. - Competitive salary, comprehensive benefits, and opportunities for professional growth.