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Ema is building an Agentic AI platform to transform enterprise productivity by enabling organizations to delegate repetitive tasks to AI agents. The company is founded by former executives from Google, Coinbase, Flipkart, and Okta, backed by leading investors including Accel, Naspers/Prosus, and Section32, with offices in Silicon Valley, London, Bangalore, and Vancouver.
In this role, you will conceptualize, develop, and deploy machine learning models that underpin Ema's NLP, retrieval, ranking, reasoning, dialog, and code-generation systems. You'll implement advanced ML algorithms including Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve AI system performance. Your responsibilities include processing and analyzing large, complex datasets (structured, semi-structured, and unstructured) to inform model development, working across the complete ML lifecycle from problem definition through deployment, implementing A/B testing and statistical validation methods, and clearly communicating technical workings and benefits to both technical and non-technical stakeholders.
You will thrive in an autonomous environment where your ideas make significant impact, solving complex problems with huge datasets while turning theoretical concepts into practical, scalable solutions. This is a mission-oriented role at a high-growth startup working at the frontier of production-grade Agentic AI systems.
REQUIREMENTS:
- Master's degree or Ph.D. in Computer Science, Machine Learning, or related quantitative field
- At least 2 years of industry experience building and deploying production-level machine learning models
- Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models
- Deep understanding of retrieval, ranking, reinforcement learning, and/or agent-based systems, with experience building them for large-scale systems
- Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch
IDEAL QUALIFICATIONS:
- Excellent skills in data processing (SQL, ETL, data warehousing) and experience with large-scale data systems
- Experience with ML model lifecycle management tools and understanding of MLOps principles
- Familiarity with cloud platforms like GCP or Azure
- Knowledge of latest industry and academic trends in ML and AI with ability to apply to practical projects
- Understanding of software development principles, data structures, and algorithms
- Excellent problem-solving skills, attention to detail, and strong logical thinking
- Ability to work collaboratively in fast-paced startup environment
