Job
Description
About Us: Athena is India's largest institution in the "premium undergraduate study abroad" space. Founded 10 years ago by two Princeton graduates, Poshak Agrawal and Rahul Subramaniam, Athena is headquartered in Gurgaon, with offices in Mumbai and Bangalore, and caters to students from 26 countries. Athena’s vision is to help students become the best version of themselves. Athena’s transformative, holistic life coaching program embraces both depth and breadth, sciences and the humanities. Athena encourages students to deepen their theoretical knowledge and apply it to address practical issues confronting society, both locally and globally. Through our flagship program, our students have gotten into various, universities including Harvard University, Princeton University, Yale University, Stanford University, University of Cambridge, MIT, Brown, Cornell University, University of Pennsylvania, University of Chicago, among others. Learn more about Athena: https://www.athenaeducation.co.in/article.aspx Role Overview We are looking for an AI/ML Engineer who can mentor high-potential scholars in creating impactful technology projects. This role requires a blend of strong engineering expertise, the ability to distill complex topics into digestible concepts, and a deep passion for student-driven innovation. You’ll help scholars explore the frontiers of AI—from machine learning models to generative AI systems—while coaching them in best practices and applied engineering. Key Responsibilities: Guide scholars through the full AI/ML development cycle—from problem definition, data exploration, and model selection to evaluation and deployment. Teach and assist in building: Supervised and unsupervised machine learning models. Deep learning networks (CNNs, RNNs, Transformers). NLP tasks such as classification, summarization, and Q&A systems. Provide mentorship in Prompt Engineering: Craft optimized prompts for generative models like GPT-4 and Claude. Teach the principles of few-shot, zero-shot, and chain-of-thought prompting. Experiment with fine-tuning and embeddings in LLM applications. Support scholars with real-world datasets (e.g., Kaggle, open data repositories) and help integrate APIs, automation tools, or ML Ops workflows. Conduct internal training and code reviews, ensuring technical rigor in projects. Stay updated with the latest research, frameworks, and tools in the AI ecosystem. Technical Requirements: Proficiency in Python and ML libraries: scikit-learn, XGBoost, Pandas, NumPy. Experience with deep learning frameworks : TensorFlow, PyTorch, Keras. Strong command of machine learning theory , including: Bias-variance tradeoff, regularization, and model tuning. Cross-validation, hyperparameter optimization, and ensemble techniques. Solid understanding of data processing pipelines , data wrangling, and visualization (Matplotlib, Seaborn, Plotly). Advanced AI & NLP Experience with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on with LLM APIs : OpenAI (ChatGPT), Anthropic, Cohere, Hugging Face. Understanding of embedding-based retrieval , vector databases (e.g., Pinecone, FAISS), and Retrieval-Augmented Generation (RAG). Familiarity with AutoML tools , MLflow, Weights & Biases, and cloud AI platforms (AWS SageMaker, Google Vertex AI). Prompt Engineering & GenAI Proficiency in crafting effective prompts using: Instruction tuning Role-playing and system prompts Prompt chaining tools like LangChain or LlamaIndex Understanding of AI safety , bias mitigation, and interpretability. Required Qualifications: Bachelor’s degree from a Tier-1 Engineering College in Computer Science, Engineering, or a related field. 2-5 years of relevant experience in ML/AI roles. Portfolio of projects or publications in AI/ML (GitHub, blogs, competitions, etc.) Passion for education, mentoring , and working with high school scholars. Excellent communication skills, with the ability to convey complex concepts to a diverse audience. Preferred Qualifications: Prior experience in student mentorship, teaching, or edtech. Exposure to Arduino, Raspberry Pi, or IoT for integrated AI/ML projects. Strong storytelling and documentation abilities to help scholars write compelling project reports and research summaries. Show more Show less
