ML Research Intern at Emotos in Remote

Summary: Emotos is an emerging AI infrastructure company focused on applying machine learning and artificial intelligence to deliver fast, secure, and efficient services. The ML Research Intern will support machine learning research through model design, experimentation, data preparation, paper review, results analysis, and documentation, while collaborating with researchers and engineers on practical ML tools and production-ready components.

Responsibilities:
- Support the design, implementation, and evaluation of machine learning models, including data preprocessing, feature engineering, and experimentation
- Reviewing research papers, prototyping algorithms, running experiments, analyzing results, and documenting findings
- Collaborate with other researchers and engineers to refine models, improve performance, and contribute to research reports or internal publications
- Building small tools or scripts to automate workflows, preparing datasets, and assisting in turning research prototypes into production-ready components

Required Qualifications:
- • Strong foundation in machine learning concepts, including supervised and unsupervised learning, model evaluation, and overfitting/regularization
- - Curiosity about adversarial ML, LLM safety, or red-teaming, even without

formal research experience
- - You read a paper and your first instinct is "let me go check that,"

not "let me go cite that"
- - Enough spare hours to actually move something forward each week, we care

about output, not hours logged
- • Proficiency in Python and common ML libraries (e.g., NumPy, pandas, scikit-learn; familiarity with PyTorch or TensorFlow is a plus)
- • Experience with data handling and analysis, including cleaning, transforming, and visualizing datasets
- • Ability to read and interpret academic papers, summarize key ideas, and translate them into implementable experiments
- • Comfort with software engineering practices such as version control (Git), reproducible experiments, and clear code documentation
- • Strong analytical, problem-solving, and quantitative skills, with attention to detail and rigor in experimentation
- • Effective written and verbal communication skills, including the ability to explain technical concepts to non-specialists
- • Currently pursuing or recently completed a degree in Computer Science, Data Science, Mathematics, Engineering, or a related field, or equivalent practical experience
- • Interest in collaborative, remote work and ability to manage time, prioritize tasks, and work independently with guidance

Preferred Qualifications:
- - Prior experience with deep learning, NLP, or representation learning is beneficial but not required

Required Skills: Machine Learning, Python, NumPy, pandas, scikit-learn, Data Preprocessing, Data Visualization, Git, Reproducible Experimentation, Research Paper Analysis

Benefits: The company supports remote collaboration., Interns receive significant ownership, mentorship, and exposure to end-to-end ML workflows., Named co-authorship on published research., Direct work with the founding team., AWS Bedrock access, an existing red-teaming pipeline, and a training corpus already in motion., A genuine path to a paid, full-time offer if the fit is there.