Distributed Systems Engineer

Role overview

This role focuses on building high-performance distributed systems for flexible, on-demand aggregation and transformation of very large datasets. You will work on core services that process terabytes of information, designing algorithms and low-latency services that support large-scale analytics and machine learning workloads.

Responsibilities

- Design and implement algorithms for fast aggregation, transformation, and processing of large datasets. - Develop compiled, production-quality systems software with a strong focus on runtime performance. - Analyze algorithmic time complexity and identify opportunities to reduce latency and resource usage. - Contribute to services that need to scale reliably across distributed environments. - Investigate and resolve performance, debugging, and system-level issues. - Help improve the application of machine learning models within high-volume data services.

Requirements

- Strong proficiency in Go. - Solid foundations in data structures, algorithms, and distributed-systems design. - Strong systems-programming background, preferably involving platform, kernel, or networking work. - Demonstrated ability to debug and troubleshoot performance and system-level problems. - Comfort reasoning in detail about optimization and computational complexity.

Nice to have

- Experience with novel data-storage formats or filesystems.

Benefits and work setup

- Remote work is supported; an office-based option is available in New York City. - The stated New York City base-salary range is $150,000–$220,000 per year, with location-based variation possible elsewhere. - Equity participation and benefits such as medical, dental, vision, and retirement may be available. - The team works on challenging data-science problems alongside experienced data scientists and engineers in a small, rapidly growing environment.