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Form of work
SalaryWho We Are
Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the AI employee. We are founded by ex-Google, Coinbase, Okta executives and serial entrepreneurs. We’ve raised capital from notable investors such as Accel Partners, Naspers, Section32 and a host of prominent Silicon Valley Angels including Sheryl Sandberg (Facebook/Google), Divesh Makan (Iconiq Capital), Jerry Yang (Yahoo), Dustin Moskovitz (Facebook/Asana), David Baszucki (Roblox CEO) and Gokul Rajaram (Doordash, Square, Google).
Our team is a powerhouse of talent, comprising engineers from leading tech companies like Google, Microsoft Research, Facebook, Square/Block, and Coinbase. All our team members hail from top-tier educational institutions such as Stanford, MIT, UC Berkeley, CMU and Indian Institute of Technology. We’re well funded by the top investors and angels in the world. Ema is based in Silicon Valley and Bangalore, India and is currently in stealth mode.
Responsibilities
Our AI Resident and Data Science Resident (North America) roles are unique opportunities for students pursuing undergraduate or graduate degrees in Computer Science and/or Electrical Engineering to get real world exposure to the latest and greatest in generative AI and data science. Our aim is to create an experience that allows you to learn how fast growing startups work, gain practical skills, build real world experience, develop a greater understanding of our industry and form valuable connections. You will join an extraordinary team, including world-class software engineers and leading machine learning practitioners who are all passionate about applying groundbreaking techniques to AI. You can work remotely. We’ll also invite some of our top residents to come and visit our San Francisco office.
A typical day to day includes reading deep learning papers, implementing described models and algorithms, adapting them to our setting and driving up internal metrics.
Research, design, implement, optimize and deploy deep learning models.
Train machine learning models.
Develop state-of-the-art algorithms in one or all of the following areas: Prompt engineering for LLM models, Fine tuning models, Training open source models, large-scale distributed training.
Comparing and benchmarking performance of different models.
Optimize deep neural networks and the associated preprocessing/postprocessing code to run efficiently on an embedded device.
Qualifications
Must be currently enrolled in a full-time degree program (BS/MS)
Expertise with and strong interest in Machine Learning or Natural Language Processing (NLP), ideally in one or more of these areas: Generative AI, Natural Language Understanding (NLU), Natural Language Generation (NLG), Structured Prediction, Unsupervised Learning & Representation Learning. Must be strong in coding skills and be ready to pick up any task and run with it.
Experience with programming languages like Python and familiarity with frameworks like
Need to be able to commit minimum 20 hours/week.
