Senior Machine Learning Engineer
$196k - $294k • Palo Alto, CA • Full-time
Posted 2mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Palo Alto, CA
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
At Klaviyo, we believe the future of software lies in systems that can run and optimize themselves based on outcome or reward metrics. We have built the infrastructure and application that serve as the interface between businesses and consumers, now serving over 200,000+ customers. We have a significant opportunity to develop state-of-the-art AI and machine learning technologies to power our products and create AI agents that can automatically generate and execute marketing strategies and campaigns. As a Senior Machine Learning Engineer, you will help build models that extract insights from massive data streams, applying cutting-edge techniques from deep learning, recommender systems, and language modeling to integrate AI into our product and deliver customer value. You will work closely with partners in Engineering, Product, and Design, and engage directly with stakeholders and customers to solve challenging problems.
Responsibilities
- Train and deploy large-scale machine learning models in production systems.
- Create AI engines or agents for automated marketing campaign generation and execution.
- Introduce conversational AI interfaces into software to enhance user efficiency.
- Build generative AI models for marketing content creation based on customer input.
- 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 leading large-scale AI/ML projects.
- Experience with machine learning frameworks like Huggingface, PyTorch, or Tensorflow.
- Experience with distributed training using Spark or Ray.
- Experience leading technical projects and collaborating with engineering teams and product managers.
- Experience developing, deploying, and maintaining machine learning models in production.
- Experience owning the full product lifecycle of ML development, including defining metrics, designing A/B tests, and iterating on results.
- Experience mentoring others.
Benefits
- Participation in the company’s annual cash bonus plan.
- Equity.
- Sign-on payments.
- Comprehensive health, welfare, and wellbeing benefits.
- Potential for up to 10% travel for onboarding, client/partner work, team meetings, and industry events.