Sr. Software Engineer - Machine Learning 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 operating at massive scale (we ingest 10 petabytes of training data per day) and our models are blazingly fast (returning predictions in 10 milliseconds or less); and a profitable unicorn (we're valued at $2B & been profitable for the last 13+ quarters). 

We are seeking an exceptional Senior Software Engineer to join us in building state-of-the-art machine learning infrastructure for our mobile advertising platform. You will be part of the engineering team that builds systems to train deep-neural-network machine learning (ML) models, as well as the infrastructure to deploy them for real-time, high-scale ad targeting.

We’re looking for a seasoned engineer to design, build and support the machine learning platforms that will power the future of Moloco’s growth. Your work will span our flagship user- and advertiser-facing products. Relevant technologies we use at Moloco include Tensorflow, Airflow, BigQuery, Dataflow, Kubernetes, Google Cloud Platform, Terraform and the C++, Go and Python programming languages.

What you'll do

• Build systems to train and serve dozens of ML models updated hundreds of times per day
• Use state-of-the-art hardware accelerators (e.g. GPUs) to optimize ML training & inference
• Deploy and respond to system alerts to maintain Moloco's real-time large-scale ML-based advertising platform in healthy operation
• Leverage your knowledge of cloud infrastructure to optimize the cost, reliability and maintainability of our platform
• Collaborate with ML modeling engineers and other partners in the company to build the best mobile advertising platform in the world

What you'll need to succeed

• 4+ years software development experience on backend/infrastructure systems, in C#, C++, Go, Java or Python
• 1+ years of cloud experience (deep expertise in using GCP, AWS and/or Azure)
• Strong Computer Science fundamentals and problem-solving skills
• Strong software development skills, from requirements to design to implementation
• Mastery of multiple skills involved in developing large scale systems such as integration testing, deployment, monitoring, production troubleshooting, database schema design, or developing data processing pipelines