Intern - Data & ML Platform
About the Role
Socure's AI Platform team is looking for a motivated summer intern to contribute to hands-on engineering work at the intersection of machine learning and production infrastructure. You'll work alongside experienced ML and platform engineers to help build and augment the systems that power how Socure trains, deploys, and serves ML models at scale.
This is a great opportunity for students who are curious about MLOps, feature engineering, model training/serving, and how cutting-edge AI systems actually make it into production and serve our customers.
What You'll Do
- Contribute to the development of scalable infrastructure for deploying and serving ML models on AWS
- Assist in building and improving CI/CD pipelines for ML workflows
- Help develop internal tools that make it easier for ML teams to deploy and monitor models
- Work with observability tooling (e.g., CloudWatch, DataDog) to monitor model performance and system health
- Collaborate closely with ML engineers, data scientists, and platform engineers to solve real problems
- Participate in code reviews and technical design discussions
What You Bring
- Currently pursuing a Bachelor's (Junior or Senior) or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field
- Solid programming skills in Python
- Excellent core CS fundamentals: data structures, algorithms, and systems concepts
- Exposure to ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Genuine interest in machine learning, AI infrastructure, or MLOps
- Strong problem-solving skills and eagerness to learn in a fast-paced environment
Nice to Have
- Coursework or project experience with cloud platforms (AWS preferred)
- Familiarity with CI/CD concepts or tools (e.g., GitHub Actions, Jenkins)
- Exposure to MLOps concepts: model versioning, experiment tracking, or deployment workflows
- Experience with SQL or NoSQL databases
- Any hands-on projects involving model training, serving, or deployment pipelines