Machine Learning Engineer, Integrity

Get AI tool; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

OpenAI in San Francisco seeks a Machine Learning Engineer to build and deploy robust ML systems that enhance product integrity, safety, and user trust at scale.

You will partner with research, product, and safety teams to craft production pipelines, train state-of-the-art models, and monitor system performance across global workloads.

Qualifications

• Strong machine learning engineering experience.
• Experience with Python and modern ML frameworks.
• Knowledge of large language models and AI systems.
• Strong software engineering fundamentals.
• Experience with distributed computing and large datasets.
• Ability to collaborate across research and engineering teams.
• Strong analytical and problem-solving skills.

Responsibilities

• Build machine learning systems for integrity and safety.
• Train and optimize production ML models.
• Detect abuse and improve policy enforcement.
• Collaborate with research and infrastructure teams.
• Deploy scalable ML services into production.
• Improve monitoring and reliability of ML systems.

Skills

ML Engineering

Python

Distributed computing

LLMs

Software engineering

Data pipelines

Collaboration

Problem solving

Tools

TensorFlow

PyTorch

Job description

OpenAI is an artificial intelligence research and deployment company dedicated to building safe artificial general intelligence (AGI) that benefits all of humanity. Founded in December 2015 in San Francisco, it is known for developing systems like ChatGPT and working on advanced AI models.

About the Role

About the Role

Develop machine learning systems that improve the integrity, safety, and trustworthiness of OpenAI products. You'll build models, evaluation pipelines, and production systems that detect abuse, improve policy enforcement, and help ensure reliable AI behavior at global scale.

The role involves close collaboration with research, product, infrastructure, and safety teams to deploy robust ML solutions into production.

Key Responsibilities

• Build machine learning systems for integrity and safety
• Train and optimize production ML models
• Detect abuse and improve policy enforcement
• Collaborate with research and infrastructure teams
• Deploy scalable ML services into productionImprove monitoring and reliability of ML systems

Qualifications

• Strong machine learning engineering experience
• Experience with Python and modern ML frameworks
• Knowledge of large language models and AI systems
• Strong software engineering fundamentals
• Experience with distributed computing and large datasets
• Ability to collaborate across research and engineering teams
• Strong analytical and problem-solving skills