OpenAI

Research Engineer, Notifications

OpenAI5 months ago
Location

San Francisco

Type

Full Time

Salary

USD 295,000 – 680,000

Level

Senior

Role

ML Engineer

Posted

Oct 8, 2025

Full TimeSenior

The role

Summary

OpenAI is seeking a Machine Learning Engineer to join their Notifications team, focused on building intelligent notification systems using both classical ML and large language models to optimize user engagement. The role involves designing ranking and recommendation systems, working at the intersection of research and product development, and requires strong ML fundamentals with experience in production-scale recommendation systems.

What you'll do

ML System Design: Design and build end-to-end ranking and recommendation systems for notifications, from modeling to evaluation and deployment
LLM Integration: Apply and adapt large language models to ranking problems, including prompt-based approaches and fine-tuning techniques
Experimentation: Develop experiments to evaluate notification relevance, user value, and long-term impact using A/B testing methodologies
Cross-functional Collaboration: Work closely with product, data science, and engineering teams to align technical solutions with business objectives
Research Integration: Collaborate with research teams to leverage cutting-edge modeling techniques while balancing production system constraints
Evaluation Systems: Build robust offline and online evaluation frameworks to measure system improvements and user outcomes
Technical Leadership: Contribute to the broader Growth ML stack and help set technical direction for intelligent user engagement systems
Model Optimization: Optimize notification systems for relevance, timeliness, and user experience across multiple channels

What we look for

Technical

ML Production SystemsHands-on experience building and deploying ranking, recommendation, or personalization systems at scale
Large Language ModelsDeep understanding of LLMs and their integration into product experiences
Statistical AnalysisProficiency in experimentation, A/B testing, and analyzing impact on user behavior and business metrics
Codebase NavigationAbility to work with large ML codebases, design evaluations, and debug complex modeling issues
Classical MLStrong foundation in traditional machine learning algorithms and techniques

Education

Advanced DegreeMaster's or PhD in Computer Science, Machine Learning, Statistics, or related quantitative field preferred
Alternative QualificationsEquivalent industry experience with demonstrated ML expertise acceptable

Experience

Production ML5+ years of experience in machine learning with focus on recommendation or ranking systems
Scaling SystemsExperience working with large-scale distributed systems and high-traffic applications
Cross-functional WorkProven track record of collaborating with product, engineering, and research teams
Fast-paced EnvironmentExperience thriving in dynamic, fast-changing startup or tech company environments

Skills

Required skills

Python ProgrammingAdvanced proficiency in Python for ML model development and data analysis
Machine Learning FundamentalsDeep understanding of ML algorithms, model training, and evaluation techniques
Ranking SystemsExperience with recommendation engines, ranking algorithms, and personalization systems
Large Language ModelsHands-on experience working with LLMs, fine-tuning, and prompt engineering
A/B TestingStatistical knowledge of experimental design and hypothesis testing
Production MLExperience deploying and maintaining ML models in production environments

Nice to have

Deep Learning FrameworksExpertise in PyTorch, TensorFlow, or similar frameworks
Cloud PlatformsExperience with AWS, GCP, or Azure for ML workloads
Distributed SystemsKnowledge of scaling ML systems across multiple nodes and clusters
Product IntuitionStrong sense of user experience and product impact of ML systems
Research BackgroundExperience with academic research or publishing in ML/AI conferences
Growth EngineeringExperience with user engagement, retention, and growth metrics

Compensation & benefits

Salary

USD 295,000 – 680,000 (annual)

Stock options

Available

Benefits

Equity Compensation

Substantial equity package with potential for significant upside in a leading AI company

Hybrid Work Model

Flexible 3 days in office per week policy with remote work options

Relocation Assistance

Comprehensive relocation package for new employees moving to San Francisco

Health Coverage

Comprehensive medical, dental, and vision insurance plans

Professional Development

Access to cutting-edge AI research and opportunities to work with world-class researchers

Learning Budget

Annual budget for conferences, courses, and skill development in AI/ML

Wellness Programs

Mental health support and wellness initiatives for work-life balance

Interview process

  1. 1
    Initial Screening — Phone or video call with recruiting team to discuss background and role fit
  2. 2
    Technical Assessment — Take-home coding challenge focusing on ML algorithm implementation and data analysis
  3. 3
    Technical Interview — Deep-dive technical discussion on ML concepts, system design, and past project experiences
  4. 4
    System Design Interview — Design a large-scale recommendation system with focus on notification ranking
  5. 5
    Cross-functional Interview — Discussion with product and research teams on collaboration and product intuition
  6. 6
    Leadership Interview — Final interview with senior leadership focusing on cultural fit and long-term vision
  7. 7
    Reference Checks — Verification of past performance and technical contributions with previous employers
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OpenAI

OpenAI

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OpenAI is an American artificial intelligence research organization developing advanced AI models like GPT. Focused on ensuring AI benefits humanity, it creates tools for natural language processing and generative AI applications.

San Francisco, California, United StatesFounded 2015openai.com

Tech Stack

Languages
PythonSQLJavaScript
Frameworks
PyTorchTensorFlowScikit-learnTransformers
Databases
PostgreSQLRedisElasticsearch
Tools
DockerKubernetesApache KafkaMLflowJupyter NotebooksGit
Other
AWS/GCPA/B Testing PlatformsMonitoring Tools

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