Staff Software Engineer - Service & Development Infrastructure

About Moloco: 

Moloco is a machine learning company empowering organizations of all sizes to grow and unlock the full value of their unique first-party data, elevating the traditional path to performance advertising. While the largest technology companies have proven the speed and scale of ad-targeting utilizing data— the same robust performance powered by machine learning has previously been unavailable beyond their platforms. 

That's where Moloco steps in. With Moloco's powerful combination of cutting-edge machine learning technologies, we play a unique and visible role in shaping the digital economy, all while allowing companies to stay independent and scale.

An industry leader at the nexus of machine learning, performance marketing, and visionary product infrastructure, Moloco is advancing the advertising technology industry. We ranked #95 in the Inc. 5000 fastest-growing private companies for 2022. We ranked #91 among Deloitte’s 2021 Fast 500 and have been certified by 91% of the company via Great Places to Work. Check us out on Glassdoor and be sure to get an inside look at working at Moloco on Instagram, Twitter, and Youtube. 

Moloco is headquartered in Silicon Valley, with offices in San Francisco, New York, Los Angeles, Seattle, London, Berlin, Seoul, Singapore, Beijing, Gurgaon, and Tokyo. 

Creating a diverse workforce and a culture of inclusion and belonging is core to our existence. To reach our goals, diversity of talent and thought is a critical component to how we operate as an organization. Our workforce is our superpower, and we know that fostering a culture of inclusion, authenticity, and belonging will allow us the greatest opportunity to carry out our mission -- to empower businesses of all sizes to grow through operational machine learning.

Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now!

About the Role

Moloco is a machine learning company that operates at massive scale (we ingest 10 petabytes of training data per day), and our models are blazingly fast (return predictions in 10 milliseconds or less); and a profitable unicorn (we are valued at $2 billion and have been profitable for the last 13+ quarters).

We are looking for an exceptional Staff Software Engineer (focused on Site Reliability) to help us build a state-of-the-art ML model serving infrastructure for our mobile advertising platform. You will be part of an engineering team that manages the infrastructure that serves deep neural network machine learning (ML) models to clients, CI/CD infrastructure to deploy infrastructure updates in real time, and develops infrastructure tools and platforms that improve the productivity of engineering teams.

We are looking for someone who is passionate about solving infrastructure problems with software engineering skills, a desire to grow and learn new technologies, a love of working in collaborative teams, and a commitment to customer service.

What you'll do

• Play a role in engineering partner teams for company-wide infrastructure adoption and standard methodologies
• Contribute to technical direction and decisions across the organization by conducting / leading research with other technical leaders in the organization
• Traditional SRE/Operational support areas such as tooling and automation, monitoring, workflow management, maintaining and improving data pipelines, CI/CD, monitoring, etc.
• Actively participate in and contribute to code reviews and technical design documents to identify performance and reliability bottlenecks.
• Partner with and support other engineering teams with operational guidance and expertise on various project initiatives.
• Participate in capacity planning and scaling
• Ensure that Moloco is delivered in a highly performant manner that can handle viral traffic spikes.
• Collaborate with others in SRE and SWE to leverage tools, processes and techniques to improve service reliability.
• Reduce business risk in areas such as infrastructure and configuration management, provisioning, capacity modeling and planning, and incident handling, mitigation, root cause analysis, and post-mortems.
• Identify common patterns in the