Machine Learning Intern Job at Ema (San Francisco Bay Area)

Machine Learning Intern

Ema

Location:
United States , San Francisco Bay Area

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

Ema is building next-generation AI 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 Universal AI employee. We’re founded by ex-Google, Coinbase, and Okta executives and serial entrepreneurs. Backed by top-tier investors and angels, we’re based in Silicon Valley and currently in stealth mode. This is a rare opportunity to work at the frontier of AI, alongside world-class founders and engineers, and contribute meaningfully to a product that could change how enterprises operate. You’ll be treated as a core member of the team—given ownership, mentorship, and the chance to turn this internship into a long-term opportunity.

Job Responsibility:

Work alongside senior ML engineers to research, build, and deploy machine learning models across NLP, retrieval, ranking, and reasoning
Prototype and experiment with LLM-based architectures and agentic systems
Help process and analyze large-scale structured and unstructured datasets
Build data pipelines, contribute to model training and evaluation, and participate in the deployment of models in production
Assist with validation experiments such as A/B testing and other evaluation methods to ensure robustness and reliability
Collaborate closely with cross-functional teams and participate in technical discussions and code reviews

Requirements:

2+ years of industry experience in a software engineering, data science, or ML role (full-time or internship)
Strong coding skills in Python and experience with ML frameworks like PyTorch or TensorFlow
A solid foundation in data structures, algorithms, and software engineering principles
Exposure to NLP, deep learning, reinforcement learning, or retrieval systems
Experience working with real-world data, and comfort with SQL and data processing pipelines
Curiosity about MLOps, cloud infrastructure, and scaling ML models
A collaborative mindset, eagerness to learn, and the ability to thrive in a fast-paced environment

Nice to have:

Working knowledge of LLM training or fine-tuning
Experience deploying models into production or contributing to shipped ML products
Familiarity with GCP, Azure, or other cloud platforms
Interest in startup culture and building 0→1 systems

Additional Information:

Job Posted:
February 21, 2026

Employment Type:

Fulltime

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