AI Developer - Graduate Intern

Data Foundations is an innovative company offering an intelligent data platform that integrates semantics, ontologies, knowledge graphs, active metadata, and agentic AI into a unified environment. This platform allows organizations to seamlessly connect diverse data sources and interact with their data using natural language queries. Users benefit from governed, explainable, and source-verified answers delivered in seconds, enabling confident decision-making and regulatory compliance. As a forward-thinking organization, Data Foundations provides opportunities to work on cutting-edge AI technologies that bridge the gap between data management and practical business applications.

Key Responsibilities

- Build and test features leveraging large language models (LLMs), including prompt design, retrieval-augmented generation (RAG), and simple agent workflows.
- Integrate AI services on AWS platforms such as Amazon Bedrock, SageMaker, Textract, and Comprehend.
- Prepare, clean, and transform data using Python and SQL, contributing to the development of robust data pipelines.
- Evaluate model outputs for accuracy, bias, and cost-effectiveness, maintaining detailed logs of results.
- Develop responsive front-end interfaces using React or similar frameworks with TypeScript.
- Create back-end APIs and services using Python frameworks like FastAPI or Flask, or Node.js.
- Manage relational and NoSQL databases, including PostgreSQL, MySQL, and DynamoDB.
- Deploy and maintain services on AWS utilizing Lambda, API Gateway, S3, ECS, and infrastructure-as-code tools such as CDK, CloudFormation, or Terraform.
- Write clean, well-tested, and documented code while actively participating in code reviews.
- Utilize Git and CI/CD pipelines to ensure safe and efficient deployment of software changes.

Required Qualifications

- Currently pursuing or recently completed a Graduate or Master’s degree in Computer Science, Data Science, AI, or a related technical discipline.
- Solid understanding of pattern recognition and neural networks, with the ability to design, train, and evaluate machine learning models.
- Familiarity with Natural Language Processing (NLP) concepts, including text processing, embeddings, and language model fundamentals.
- Knowledge of AI/ML fundamentals, statistics, and model evaluation methodologies.
- Experience with machine learning and NLP libraries such as PyTorch, TensorFlow, scikit-learn, spaCy, or Hugging Face is advantageous.
- Comfortable working remotely within a collaborative team environment, using version control systems like Git and following agile development practices.
- Strong analytical skills, clear technical communication abilities, and a keen interest in learning emerging AI and data technologies.

This role offers the chance to engage with state-of-the-art AI tools and contribute to a platform that transforms how organizations leverage their data. Candidates who are passionate about AI and data science, eager to grow their skills, and thrive in a dynamic, remote work setting will find this opportunity rewarding.