Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Experience Requirements:

• 4+ years of experience supporting the infrastructure within an ML environment

Other Requirements:

• Experience in developing tools used to diagnose ML infrastructure problems and failures

• Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage)

• Experience working with GPUs

Responsibilities:

• Provide infrastructure support to our ML research and product

• Build tooling to diagnose cluster issues and hardware failures

• Monitor deployments, manage experiments, and generally support our research

• Maximize GPU allocation and utilization for both serving and training

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Education Requirements:

• at least PhD (or equivalent) research experience

Other Requirements:

• Write clear and clean production-facing and training code

• Experience working with GPUs (training, serving, debugging)

• Experience with data pipelines and data infrastructure

• Strong understanding of modern machine learning techniques (reinforcement learning, transformers, etc)

• Track-record of exceptional research or creative applied ML projects

Responsibilities:

• Develop alignment algorithms and loss functions

• Write data pipelines to process diverse web data

• Identify quality signals to understand our model’s performance

• Design sampling algorithms to improve serving efficiency

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Education Requirements:

• preferably 2+ years of industry experience

Other Requirements:

• Deep understanding of the “whole stack” when it comes to designing, training, evaluating and deploying machine learning models

• Have a track record of successfully owning projects from start to finish

• Have experience with generative models for various modalities

• Experience working with proven tools

• Experience working with diffusion models

Responsibilities:

• Determining the type of training data we need

• Developing new model architectures

• Creating new evaluations

• Writing fast inference algorithms

• Working with product teams to integrate feedback mechanisms into the product

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Education Requirements:

• B.A.S. in Computer Science or equivalent experience

Experience Requirements:

• 5+ years of industry experience

Other Requirements:

• Experience building/consuming RESTful and gRPC based web-services

• Experience building and managing infrastructure in a cloud environment (GCP, AWS or Azure)

• Familiar with one of the popular ML Frameworks like Pytorch, Tensorflow

• Experience writing highly performant service in a modern typed language

• Experience configuring and maintaining CI/CD pipelines and automated testing

Responsibilities:

• Work cross functionally with product, data science, data platform and ML researchers

• Identify, design and implement the applied ML infra

• Lead implementation of our ML backend systems

• Support scaling our existing systems

Benefits:

• Competitive salary

• Equity

• Remote work option

Experience Requirements:

• 3+ years of experience

Responsibilities:

• Develop and maintain backend infrastructure

• Build and improve AI models

• Work with frontend engineers to integrate AI features

Benefits:

• Competitive salary

• Equity

• Remote work option

Experience Requirements:

• 3+ years of experience

Responsibilities:

• Develop and maintain frontend infrastructure

• Work with backend engineers to integrate AI features

• Improve user experience