Senior Machine Learning Platform Engineer (Platform)

About Us

At Coinbase, our mission is to increase economic freedom in the world. It's a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system.

To achieve our mission, we're seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up. We want someone who will run towards, not away from, solving the company's hardest problems.

Our work culture is intense and isn't for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there's no better place to be.

While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.

The Role

We are looking for a Senior Machine Learning Platform Engineer to join our Machine Learning Platform team. The team builds the foundational components for feature engineering and training/serving ML models at Coinbase. Our platform is used to combat fraud, personalize user experiences, and to analyze blockchains. You will get the opportunity to apply your engineering skills across all aspects of building ML at scale: stream processing, distributed training, and highly available online services.

Responsibilities

• Form a deep understanding of our Machine Learning Engineers' needs and our current capabilities and gaps.
• Mentor our talented junior engineers on how to build high quality software, and take their skills to the next level.
• Continually raise our engineering standards to maintain high-availability and low-latency for our ML inference infrastructure that runs both predictive ML models and LLMs.
• Optimize low latency streaming pipelines to give our ML models the freshest and highest quality data.
• Evangelize state-of-the-art practices on building high-performance distributed training jobs that process large volumes of data.
• Build tooling to observe the quality of data going into our models and to detect degradations impacting model performance.

Requirements

• 5+ years of industry experience as a Software Engineer.
• A strong understanding of distributed systems.
• Lead by example through high quality code and excellent communication skills.
• A great sense of design, and can bring clarity to complex technical requirements.
• Treat other engineers as a customer, and have an obsessive focus on delivering them a seamless experience.
• Mastery of the fundamentals, such that you can quickly jump between many varied technologies and still operate at a high level.

Nice to Have

• Experience building ML models and working with ML systems.
• Experience working on a platform team, and building developer tooling.
• Experience with the technologies we use (Python, Golang, Ray, Tecton, Spark, Airflow, Databricks, Snowflake, and DynamoDB).

Compensation

Depending on your work location, the target annual base salary for this position can range from $186,065 to $225,000 USD. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, vision and 401(k)).