About the company
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo brings to our workplace. We believe everyone deserves a fair shot at success. Klaviyo empowers creators to own their destiny by making first-party data accessible and actionable like never before.
About the role
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.
Responsibilities
- Train and deploy large-scale Machine Learning models in production systems.
- Create AI engines or agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns.
- Introduce conversational AI interfaces into our software.
- Build generative AI models that can automatically generate content for marketing.
- Work in high impact environments with fast experimentation and product development cycles.
Requirements
- 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.
- 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.
- Experience 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.
- 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.