AI Intern – Entry Level Artificial Intelligence Internship
You will contribute to production-bound AI projects from day one. Within a supportive, remote-first environment, you’ll clean diverse data sets, write utility scripts, test neural-network prototypes, and document repeatable workflows. Expect rapid feedback loops—your code improvements can go live in a single sprint!
What You’ll Do
- Clean, normalize, and annotate structured and unstructured data.
- Create concise Python scripts that automate data ingestion, ETL, and metric collection.
- Evaluate TensorFlow and PyTorch models, logging precision, recall, and latency.
- Debug elementary issues in Jupyter notebooks, RESTful APIs, and CI pipelines.
- Draft readable documentation and flowcharts that demystify model behavior for non-technical stakeholders.
- Assist researchers with literature reviews, experiment setup, and reproducibility checks.
- Track datasets, model versions, and experiment parameters inside MLflow or Weights & Biases.
- Pair-program with senior machine-learning engineers to refactor legacy code into modular components.
- Present weekly progress in stand-ups, adapting communication style for cross-functional audiences.
- Stay current on emerging AI regulations, fairness guidelines, and ethical best practices.
What You Bring
- Bachelor’s degree in Computer Science, Data Science, or related discipline earned within the last three years.
- Proficiency in Python fundamentals (lists, comprehensions, virtual environments, pytest).
- Coursework or project exposure to machine learning basics—classification, regression, overfitting mitigation.
- Familiarity with TensorFlow or PyTorch; the curiosity to compare both.
- Solid grasp of data wrangling libraries such as pandas and NumPy.
- Comfort using Git, GitHub Actions, and Docker for reproducible environments.
- Analytical mindset—eager to inspect metrics, spot anomalies, and articulate findings.
- Collaborative spirit; you enjoy pair coding, code reviews, and knowledge sharing.
- Adaptability to remote collaboration tools (Slack, Zoom, Miro) while maintaining clear, concise communication.
- Self-directed learning habit—one side project or Kaggle notebook that showcases initiative.
Why This Team
A compact, venture-backed product group blends research agility with production rigor. You will learn from mentors who have scaled AI solutions in finance, healthcare, and retail. Expect autonomy—plus structured guidance—to build an impressive portfolio that opens doors to machine-learning engineering, data science, or MLOps roles.
Ready to solve real-world problems with algorithms that matter? Apply now and start shaping tomorrow’s intelligent systems.