Intern - Machine Learning

About the Role

The role entails working across the stack, from data pipelines and model experimentation to integrating LLMs into live products. This is an ideal position for someone who enjoys the challenge of applied AI, moving beyond theoretical models to help ship real, production-grade agent systems. The fast-paced environment requires the ability to experiment, learn independently, and prototype features quickly in a production environment.

Goodlight AI is committed to fostering a culture of innovation and learning. As an intern, you will have the opportunity to contribute to internal tooling for model monitoring, evaluation, and iteration, ensuring that your skills and knowledge are constantly evolving.

What You Will Do

• Build and experiment with ML models and LLM-powered systems, focusing on applications such as classification, embeddings, retrieval, and agents.
• Work on real-world use cases including retail personalization, workflow automation, and customer intelligence, applying machine learning to drive impactful solutions.
• Design and improve prompt pipelines, evaluation frameworks, and agent behaviors to enhance the performance and efficiency of AI systems.
• Collaborate on data pipelines, including ingestion, cleaning, feature engineering, and analysis, to ensure high-quality data for model training.
• Prototype and ship features quickly in a production environment, leveraging your ability to work independently and as part of a team.
• Contribute to internal tooling for model monitoring, evaluation, and iteration, furthering the development of AI capabilities.
• Participate in the development of intelligent agents that automate complex workflows, applying your knowledge of machine learning and software development.
• Work closely with the founding team on high-impact problems, ensuring your contributions are valued and recognized.
• Engage in continuous learning, expanding your skills in machine learning, Python, and data engineering to stay up-to-date with industry developments.

What We Are Looking For

• Strong fundamentals in machine learning and statistics, with a solid understanding of theoretical concepts and practical applications.
• Hands-on experience with Python and ML libraries such as PyTorch, scikit-learn, demonstrating your ability to apply machine learning to real-world problems.
• Familiarity with LLMs, embeddings, vector databases, or agent frameworks, with a keen interest in exploring their applications in AI systems.
• Comfort working with APIs and integrating ML into applications, showcasing your ability to collaborate across disciplines.
• Ability to move fast, experiment, and learn independently, with a strong passion for applied AI and its potential to drive innovation.
• Clear thinking and the ability to translate messy problems into structured solutions, leveraging your analytical and problem-solving skills.
• Experience with data engineering concepts such as SQL, pipelines, and ETL, highlighting your understanding of data management and analysis.

Nice to Have

• Experience building AI agents or working with tools like LangChain, OpenAI APIs, etc., demonstrating advanced skills in AI development.
• Exposure to retail, ecommerce, or customer data problems, showcasing your ability to apply machine learning in diverse contexts.
• Side projects or demos that showcase applied ML work, highlighting your creativity and initiative in exploring machine learning applications.

Benefits and Perks

• Direct exposure to building cutting-edge AI agents and production systems, with the opportunity to contribute to innovative projects.
• Opportunity to work closely with the founding team on high-impact problems, ensuring your contributions are recognized and valued.
• Ownership of real features that go live to users, providing a sense of accomplishment and impact.
• Fast learning environment with high autonomy, allowing you to grow professionally and personally.
• Remote work arrangement, offering flexibility and work-life balance.
• Potential for full-time conversion based on performance, providing a clear path for career advancement.

• Ensure you have a strong foundation in machine learning and statistics, and be prepared to discuss your understanding of these concepts during the interview.
• Showcase your experience with Python and ML libraries by sharing projects or code examples that demonstrate your skills.
• Highlight your ability to work independently and as part of a team, emphasizing your communication and collaboration skills.
• Be ready to discuss how you approach problem-solving and translating complex problems into structured solutions, using specific examples from your experience.
• Prepare to talk about your experience with data engineering concepts and how you have applied them in previous roles or projects.
• If possible, share side projects or demos that demonstrate your applied ML work, as this can significantly enhance your application.
• Research Goodlight AI and its focus on building intelligent agents, preparing thoughtful questions to ask during the interview about the company and the role.