Senior Machine Learning Engineer

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. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.

Sr. Machine Learning Engineer

Palo Alto, CA (Onsite 5x a week)

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 Sr. Machine Learning Engineer at Klaviyo, you will help build models that extract insights from the massive streams of data that Klaviyo ingests continuously. You will apply cutting-edge techniques from deep learning, recommender systems, language modeling, and more to integrate artificial intelligence into our product and bring customers value. You will need to deep dive into the product and the code to understand and contribute to solutions with your technical knowledge and experiences. You will be working with partners in Engineering, Product, and Design to solve challenging problems, and talking to stakeholders and customers firsthand.

Things you’ll do & make a difference

• Train and deploy large-scale Machine Learning models in production systems to improve the values our product provide to our customers


• Create AI engines or agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business and demonstrably outperform our human customers at Klaviyo.


• Introduce conversational AI interfaces into our software to make our customers more efficient users of our products.


• Build generative AI models that can automatically generate content for marketing given customer input on context, to maximize customer ROI or improve customers’ productivity.


• Work in high impact environments with fast experimentation and product development cycles

What we are looking for:

• Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.


• 5+ years of experience in AI, machine learning, or related fields, with a track record of successfully leading large-scale AI / machine learning projects launched in products with a significant impact on users / customers.


• Experience with machine learning frameworks such as Huggingface, PyTorch, Tensorflow, Keras; Experience with distributed training with Spark, Ray, etc.


• Experience leading technical projects and working with engineering teams and product managers successfully to deliver customer-facing features


• Experience of developing and putting machine learning models into production, while also owning and maintaining production models long term


• Experience owning the full product lifecycle of ML development, including defining success metrics, designing and analyzing A/B tests, and iterating based on result


• Experience mentoring others

Nice to have:

• Experience with recommendation systems, including designing, training, and deploying recommendation models, as well as building retrieval and ranking systems.


• Experience working in B2B businesses and interacting with customers directly


• Experience developing technical roadmaps for solving complex business problems using Machine Learning


• Experience fine-tuning and productionizing transformer-based models at scale, particularly large language models.