Machine Learning Engineer Internship-Summer 2027

Klaviyo Campus • Palo Alto, CA

2d • $65 - $65 • Onsite

About The Position

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 200,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We have a big opportunity to build state-of-the-art AI and machine learning technologies at Klaviyo to power our products and develop AI agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business. As a Machine Learning Engineer Intern at Klaviyo, you will work with a team of Machine Learning and Full-stack engineers to build models that extract insights from the massive streams of data that Klaviyo ingests continuously. You will apply cutting-edge techniques from deep learning, language modeling, recommender systems, and more to integrate artificial intelligence into our product and bring customers value. You will be a contributing member of the team, learning from experienced engineers and helping to set the standard for excellence. You should have foundational knowledge in machine learning or data science, especially in the domain of deep learning, recommender systems, NLP, generative AI, or related areas.

Requirements

• Pursuing an advanced degree Phd preferred in Computer Science, Artificial Intelligence, Machine Learning, or a related field, Graduating in December 2027 or May/June 2028
• Previous internship experience in AI, machine learning, or related fields, with a strong interest in building and deploying machine learning projects.
• Familiar with large-scale data processing techniques.
• Good communication skills, capable of collaborating with team members and learning from stakeholders.
• Foundational understanding through prior internships and projects of AI technologies and their application in business contexts, including deep learning, recommendation systems, NLP, generative AI, or related areas.
• Ability to code in Python and use standard ML technologies such as PyTorch.

Nice To Haves

• Experience with large-scale data processing tools including Spark

Responsibilities

• Build high-impact ML systems, tackling challenges such as model development, deployment, and scale, with direct ownership of high impact systems.
• Contribute to the modeling & system design and implementation decisions.
• Contribute to the development and execution of technical strategies that align with Klaviyo's business goals, ensuring products are not only exceptional but also aligned with the broader vision for a reliable and user-friendly AI/ML platform.
• Engage with internal stakeholders to understand their needs and resolve blockers.
• Learn and improve upon engineering-wide processes like recruiting, performance development, communication, and agile development.
• Stay abreast of emerging AI trends and technologies, identifying and leveraging opportunities for their application within Klaviyo’s ecosystem.
• Work with the team on project planning and defining achievements, identifying dependencies, and meeting business goals.

Benefits

• 11-week paid experience
• Lunch is on us 5 days a week
• free snacks and drinks
• social events beyond team and project work: game nights, ice cream socials, and Ask Me Anything sessions with Klaviyo's senior leadership
• comprehensive range of health, welfare, and wellbeing benefits

What This Job Offers

• Career Level: Intern