Senior Machine Learning Engineer, Reliability

jobr.pro; San Mateo (CA); On-site; USD 196,750 - 243,290; Full time

Benefits offered by this job

Equity compensation

Comprehensive benefits

Job summary

Roblox is seeking a Senior Machine Learning Engineer in San Mateo, California, to enhance system reliability using cutting-edge machine learning techniques. Responsibilities include defining the ML roadmap, improving real-time anomaly detection, and developing methods for data consumption.

This role requires strong distributed systems knowledge and the ability to communicate complex concepts effectively. The annual salary ranges from $196,750 to $243,290, alongside equity compensation and benefits.

Qualifications

• Expert in various modeling techniques with the ability to fine-tune models.
• Understanding of large-scale high-throughput systems.
• Ability to propose infrastructure for implementing learning systems.

Responsibilities

• Define the roadmap for leveraging Machine Learning Engineering.
• Improve anomaly detection capabilities using ML techniques.
• Build pipelines to consume various streams of data.
• Develop reasoning layers to find root causes of problems.
• Create time-series models for automated scaling.

Skills

Machine Learning techniques

Distributed systems fundamentals

Data analysis

Job description

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

Why Reliability?

Roblox serves over 100 million people every day across a platform that is constantly evolving — and behind every experience is infrastructure that has to work, every time, at massive scale. The Reliability team at Roblox operates at the depth and breadth of the Roblox stack. Availability of the platform is a key company goal. We are hiring our first Senior Machine Learning engineer within our team.

As a Senior Machine Learning Engineer within Reliability, you will help set the direction for how machine learning systems/practices can be leveraged to improve the reliability of the overall Roblox platform. You will own the architectural and execution roadmap of leveraging massive data across logs, traces, metrics, production changes, to proactively detect issues before they become real problems (MTTD) and/or reduce time to resolve incidents (MTTR). You will have the opportunity to cross functionally collaborate with other similar teams at Roblox to define best practices and software.

You will:

• Help define the roadmap for leveraging Machine Learning Engineering to improve Production Systems Reliability at Roblox.
• Improve realtime anomaly detection capabilities by leveraging various state‑of‑the‑art ML techniques, thereby directly contributing to improving Mean Time to Detect Production issues.
• Develop methods to build pipelines to consume various streams of data (metrics, logs, traces, change management systems etc.).
• Build a reasoning layer that interacts with the streams of data to find possible root causes of problems happening in production.
• Build time‑series models to predict capacity exhaustion and seasonal traffic spikes to drive automated scaling.

You have:

• Beyond off the shelf: We are looking for an expert who has knowledge of various modeling techniques, ability to go deep and fine‑tune models to fit our use cases.
• Ability to propose and architect the infrastructure that allows us to implement systems that learn from user and/or automated feedback.
• Good distributed systems fundamentals and understanding of large‑scale high‑throughput systems.

You are:

• Comfortable with Ambiguity: You thrive in undefined or open‑ended problem spaces, providing structure, clarity, and decisive direction to your teams.
• A Pragmatic Builder: You are scrappy and impact‑oriented. You view undefined data and messy systems as opportunities to build structure rather than blockers to progress.
• An Executive Communicator: Highly effective at communicating complex technical concepts to both engineering teams and non‑technical executive leadership.
• Data & System Oriented: You understand that robust data and systems are the foundation of any production application, and you design infrastructure for scale, correctness, and reliability.
• Curious & Creative: You enjoy tackling hard problems, exploring new technologies, and driving continuous improvements in both systems and workflows.

Annual Salary Range

$196,750 — $243,290 USD

All full‑time employees are also eligible for equity compensation and for benefits as described on this page.

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.

For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H‑1B sponsorship at this time.