About the job
Who We Are
Ema is pioneering a revolutionary AI technology aimed at empowering every employee within the enterprise to unlock their full potential in creativity and productivity. Our proprietary technology enables companies to automate repetitive tasks, allowing their workforce to focus on more impactful work. Founded by former executives from Google, Coinbase, and Okta, as well as seasoned entrepreneurs, we have attracted investment from prominent backers including Accel Partners, Naspers, Section32, and renowned Silicon Valley Angels like Sheryl Sandberg, Divesh Makan, Jerry Yang, Dustin Moskovitz, David Baszucki, and Gokul Rajaram.
Our team is a powerhouse of exceptional talent, featuring engineers from top tech giants like Google, Microsoft Research, Facebook, Square/Block, and Coinbase. Our members hail from prestigious institutions such as Stanford, MIT, UC Berkeley, CMU, and the Indian Institute of Technology. With robust funding from elite investors and angel backers, Ema operates from Silicon Valley and Bengaluru, India. This position offers a hybrid work model, requiring employees to work from the office three days a week.
Who You Are
We seek innovative and passionate Machine Learning Engineers eager to join our dynamic team. You thrive on solving complex challenges, relish working with substantial datasets, and excel at transforming theoretical concepts into scalable practical solutions. As a collaborative team player, you also flourish in independent environments where your ideas can drive significant change. You are excited about leveraging machine learning techniques to explore the frontiers of Natural Language Processing, Information Retrieval, and related technologies. Most importantly, you are enthusiastic about contributing to a mission-driven, high-growth startup poised to make a lasting impact.
Your Responsibilities
- Conceptualize, develop, and deploy machine learning models that serve as the backbone of our NLP, retrieval, ranking, reasoning, dialogue, and code-generation systems.
- Implement cutting-edge machine learning algorithms, including Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems, to enhance the performance of our AI solutions.
- Lead the processing and analysis of large, complex datasets (structured, semi-structured, and unstructured) and utilize insights to refine our model development.
- Engage across the complete lifecycle of ML model development — from problem definition and data exploration to feature engineering and model evaluation.

