As an AI Engineer Intern, you'll be part of a dynamic team focused on developing, refining, and deploying core AI features for our proprietary AI-driven products and solutions. You'll bridge the gap between AI research and application, translating innovative concepts into tangible, impactful features.

Key Responsibilities:

• Collaborate with cross-functional teams to design, develop, and implement AI features, focusing on areas like natural language processing, data analysis, and predictive modeling.

• Conduct research and rapid prototyping of the most suitable AI algorithms and techniques based on best practices, particularly those involving LLMs to address technical and business requirements.

• Write clean, well-tested, and well-documented code, contributing to efficient and maintainable system components.

• Contribute to the project's foundational knowledge by documenting the shared technical understanding and implementation details aligned with high-level business requirements and project goals.

Qualifications:

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence or a related field.

• You are a team player that enjoys collaborating and communicating with diverse groups.

• You enjoy tackling large challenges and enjoy discovering problems as much as solving them.

• You are able to problem solve and adapt to changing priorities in a fast-paced dynamic environment.

• Able to commit to a 6 months full time internship duration.

• This is a full work-from-office (WFO) internship.

Skills You’ll Need to Bring:

• You have built or prototyped features with AI technologies (LLMs, Embeddings, Fine-Tuning).

• You have experience in agentic frameworks (e.g., ADK, LangChain) for building LLM-powered applications.

• You have strong technical skills in Python.

• You are adept at optimizing, refactoring, and improving Python code, ensuring our systems are efficient, scalable, and maintainable

Nice to Haves:

• Hands-on experience with cloud platforms (GCP).

• Demonstrated interest in advanced AI topics such as Reinforcement Learning (RL).

• Familiarity with processing multi-modal data (audio and video).

• Familiarity with Agile development methodology and collaboration tools (e.g., JIRA) for task management and sprint planning.