About GitHub

As the global home for all developers, GitHub is the complete AI-powered developer platform to build, scale, and deliver secure software. Over 100 million people, including developers from 90 of the Fortune 100 companies, use GitHub to build amazing things together across 330+ million repositories. With all the collaborative features of GitHub, it has never been easier for individuals and teams to write faster, better code.

Locations

In this role you can work from Remote, United States

Overview

GitHub is changing the way the world builds software and we want you to help build and secure GitHub. We're looking for an experienced machine learning expert to help train, test and deploy models as well as conduct ad-hoc analysis as they protect the home of all developers.

You will be responsible for identifying new trends relating to safety, fraud and abuse on GitHub, building models to detect this abuse at scale, identifying vulnerabilities in GitHub that lead to abuse and helping to measure the impact of our work to safeguard the platform. At GitHub, Platform Health’s mission is to ensure GitHub’s platform safety through fighting malware, spam and fraud, monitoring for fake accounts, countering inauthentic content, battling crypto mining, and other core areas. You will be involved in collaborations across teams within GitHub including with CoPilot and setting the standard for effective and responsible use of AI for moderation and trust and safety purposes ensuring fraud is countered, content is moderated, users are kept safe and the open-source community can flourish.

If you have a foundation in online platform trust and safety issues, skills in data science and machine learning and an empathetic approach to mentoring and collaborating with a diverse team from entry-level associates to seasoned senior contributors then this might be the gig for you.

Responsibilities

• Conduct thorough analysis of data to identify patterns, trends, and anomalies that indicate potential risks or fraudulent behavior.
• Develop and implement machine learning models and algorithms to detect and prevent fraudulent activities, abuse, and security threats.
• Utilize Azure Machine Learning services and other relevant technologies to build scalable and reliable machine learning workflows.
• Documenting the systems you help build.
• Encouraging the technical growth of your peers.
• Collaborate closely with cross-functional teams including data scientists, software engineers, product managers and content moderators to integrate machine learning solutions into production systems.
• Evaluate and improve existing machine learning models and algorithms based on performance metrics and feedback from operational deployments.
• Identifying the vulnerabilities in products that lead to abuse.
• Reviewing new products and providing consultation to product teams.
• Stay updated with the latest advancements in machine learning, fraud detection techniques, and security protocols to continuously enhance our capabilities.
  
  

Qualifications

Required Qualifications

• 2+ years of experience operationalizing machine learning and data science.
• 1+ year experience in any of these technologies: GraphQL, Flink, Python, SQL, Azure Machine Learning, Kusto.
• 1+ year experience in Data Visualization, Data Storytelling or other strong written and verbal communication skills.
  
  

Preferred Qualifications

• Experience in Trust and Safety, National Security or fighting spam, malware, fraud, and threat actor activity at scale.
• Experience in responsible AI.
• Experience in Safety-by-Design.
• Strong understanding of machine learning algorithms (supervised and unsupervised learning, anomaly detection, etc.) and their practical implementation.
• Excellent problem-solving skills and the ability to translate business requirements into technical solutions.
• Experience in deploying machine learning models in production environments.
  
  

Compensation Range

The base salary range for this job is USD $75,000.00 - USD $198,900.00 /Yr.

These pay ranges are intended to cover roles based across the United States. An individual's base pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant. At GitHub certain roles are eligible for benefits and additional rewards, including annual bonus and stock. These rewards are allocated based on individual impact in role. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee's role.

GitHub values

• Customer-obsessed
• Ship to learn
• Growth mindset
• Own the outcome
• Better together
• Diverse and inclusive
  
  

Manager fundamentals

• Model
• Coach
• Care
  
  

Leadership principles

• Create clarity
• Generate energy
• Deliver success
  
  

Who We Are

GitHub is the world’s leading AI-powered developer platform with 100 million developers and counting. We’re also home to the biggest open-source community on earth (and 99% of the world’s software has open-source code in its DNA). Many of the apps and programs you use every day are built on GitHub.

Our teams are dreamers, doers, and pioneers, leading the way in AI, driving humanitarian efforts around the globe, and even sending open source to Mars (and beyond!). At GitHub, our goal is to create the space you need to do your best work. We’re remote-first and offer competitive pay, generous learning and growth opportunities, and excellent benefits to support you, wherever you are—because we know that people flourish when they can work on their own terms.

Join us, and let’s change the world, together.

EEO Statement

GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate!