About Company We are a well-funded Generative AI startup committed to crafting exceptional, human-centered conversational experiences for consumers worldwide. Our mission is to make AI interactions more accessible, impactful, and engaging by combining advanced Generative AI with intuitive, human-centered design. Our team is led by industry veterans with deep expertise in AI, personalization, and NLP, with experience at top global tech firms. About The Role We are seeking an AI / ML Engineer with a strong foundation in ML theory and a drive to apply it in real-world, user-facing applications. Whether you’re an experienced engineer or a mathematically deep data scientist ready to step into an IC role, this position gives you the opportunity to turn cutting-edge ideas into production-grade systems. You’ll work closely with product and engineering teams to solve complex modeling challenges, from user understanding and prediction to behavioral signals and search quality. This is a hands-on, builder-friendly role for someone who enjoys thinking deeply and coding fast. We’re looking for someone who Has a strong grasp of traditional machine learning algorithms, their mathematical foundations, and trade-offs. Can confidently evaluate and experiment with SOTA techniques (transformers, graph models, ensemble methods, etc.) Brings curiosity and foundational understanding of LLMs and how they work under the hood, from architecture to fine-tuning and prompt strategies & is eager to deepen this knowledge through real-world applications May not have shipped many large systems but can think rigorously, write clean code, and learn systems as needed Contribute to the creation of a high-quality data and experimentation pipeline like user behavior modeling, or recommendation systems Experienced in working with real-world datasets from data cleaning and feature engineering to exploratory analysis and insight generation Is comfortable playing a hands-on individual contributor role directly through experimentation, implementation and optimization in a fast-moving environment. Curiosity to explore different modeling approaches and apply them across a wide range of product problems Requirements 4+ years of experience, including familiarity with Node.js and/or Python. Bachelor's degree in Computer Science or related field from a top-tier institution (e.g., IIT, BITS, NIT, IIIT). Strong grasp of ML fundamentals and experience with model development or data-driven systems. Demonstrated ability to write high-quality code, reason through complex systems, and work independently. Experience building or experimenting with machine learning pipelines or services. Humble, collaborative mindset , eager to learn, contribute, and help the team win together. Nice to Have Prior exposure to NLP, user modeling, search, or ranking problems. Experience with ML tools/frameworks like PyTorch, TensorFlow, scikit-learn Knowledge of modern data stacks (e.g., vector databases, feature stores) Experience working in a startup or agile R&D setting Passion for building in India-first consumer markets, especially if you have an interest in culture, spirituality, or wellness. Why Join Us? Build real impact: Work on a fast-scaling product loved by thousands and growing Ownership & autonomy: Your ideas and execution will directly shape the product Learn from the best: Collaborate with experts in AI, product, and design Fast growth: Room to grow technically and professionally in a high-velocity environment Purpose-driven: Help create a platform that blends technology with cultural relevance If you’re excited about solving deep learning and modeling problems with real-world consequences, and want to do that in a fast, human, and ambitious team - let’s talk. 🚀 Skills: mathematical foundations,modeling problems,scikit-learn,vector databases,machine learning,node.js,recommendation systems,ai,user behavior modeling,exploratory analysis,sota techniques,nlp,real-world datasets,pytorch,fast-scaling product,feature engineering,data-driven systems,data cleaning,tensorflow,model development,python,ml theory,ml fundamentals,experimental design Show more Show less
