August 26
• As our Staff Systems Engineer specializing in Rust, you will play a pivotal role in shaping our technology landscape. • Your primary responsibilities will include designing, developing, and implementing system libraries in Rust, which will be complemented by C++ and Go. • An active contributor to our GitHub repositories, you'll uphold best practices in software development and occasionally delve into compiler development, using tools like LLVM. • Your role extends beyond technical expertise to facilitating cross-functional collaboration and strategic thinking, aiming to innovate and enhance our systems engineering continuously.
• Expert-level experience in Rust programming or C++ as a secondary language • Solid understanding of systems programming and computer architecture • Familiarity with Protocol Buffers, Capn’Proto, or FlatBuffers • Background in compiler development or systems programming • Hands-on experience with managing GitHub Open Source projects • Working knowledge of other programming languages (Polyglot) • Previous experience in Blockchain technology • Familiarity with Zero-Knowledge Proofs • Experience with LLVM (bonus)
• Competitive range of $288,000 - $330,000 • Access to leadership coaching and numerous learning opportunities. • Remote work with up to 20% travel for team meetings and events, plus a Seattle co-working space. • Comprehensive coverage with United Health Care Choice Plus (US employee), including significant premium contributions. Gold-level insurance for international employees via Deel. • 401k to support your future or statutory plans in your given country. • Generous company equity via Profit Incentive Units (PIUs), vesting monthly. • Unlimited PTO, with 3-5 weeks standard. • 11 paid holidays for rest and rejuvenation (US). • A supportive, collaborative, and inclusive work environment.
Apply NowAugust 9
501 - 1000
Manage Windows infrastructure and support Microsoft 365 implementations and operations.
August 9
5001 - 10000
Develop robust Java solutions for information retrieval and processing in a cloud environment.
July 18
2 - 10
Optimize deployment of AI models on diverse edge hardware platforms for efficient performance.