Gensyn
Software Engineer, Backend
Job Summary
This role involves building and maintaining software components for the Gensyn network to solve complex distributed machine learning problems. Candidates should have strong computer science fundamentals and experience with distributed systems, system-level programming, and performance optimization. The position emphasizes architectural contributions, system design, code quality, and working with AI systems in production environments. It offers remote work, competitive benefits, and opportunities for growth within a cutting-edge neural network infrastructure.
Required Skills
Benefits
Job Description
Machine intelligence will soon take over humanity’s role in knowledge-keeping and creation. What started in the mid-1990s as the gradual off-loading of knowledge and decision making to search engines will be rapidly replaced by vast neural networks - with all knowledge compressed into their artificial neurons. Unlike organic life, machine intelligence, built within silicon, needs protocols to coordinate and grow. And, like nature, these protocols should be open, permissionless, and neutral. Starting with compute hardware, the Gensyn protocol networks together the core resources required for machine intelligence to flourish alongside human intelligence.
The Role
- Build the software components that make the Gensyn network solve complex distributed machine learning problems
Responsibilities
- Contribute to and maintain the Gensyn executor, mesh network, and SDK, adding new features, optimizing existing solutions, fixing bugs, and participating in the architectural evolution of the system
- Contribute to system architecture and design decisions for large-scale deployments
- Conduct code and design reviews to uphold high standards of code quality across the team
- Measure and optimize existing components to ensure they meet end-user requirements effectively
Competencies
Must Have
- Rock solid computer science fundamentals
- Demonstrable production experience shipping code
- Proficient in one system-level language (e.g. Go, C/C++, Zig, Rust…)
- Deep understanding of distributed systems or systems at scale
- Operating system fundamentals - preferably Linux/macOS
- Highly self-motivated with excellent verbal and written communication skills
Preferred
- Experience with common networking protocols and/or execution environments
- Experience working in high-growth start/scale-up environments
- Experience working with observability tools, such as metrics and traces
- Experience with building distributed databases, file systems, or queues
Nice to have
- Experience with AI systems in production
- Experience contributing to or maintaining open-source distributed systems
- Proficient in Golang
- Performance optimization tooling and tactics experience
- Proficient understanding of distributed systems concepts (Consensus, CAP, Fault Tolerance)
- Experience with UNIX/POSIX APIs
Compensation / Benefits
- Competitive salary + share of equity and token pool
- Fully remote work - we currently hire between the West Coast (PT) and Central Europe (CET) time zones
- Visa sponsorship - available for those who would like to relocate to the US after being hired
- 3-4x all expenses paid company retreats around the world, per year
- Whatever equipment you need
- Paid sick leave and flexible vacation
- Company-sponsored health, vision, and dental insurance - including spouse/dependents [🇺🇸 only]
Our Principles
Autonomy & Independence
- Don’t ask for permission - we have a constraint culture, not a permission culture.
- Claim ownership of any work stream and set its goals/deadlines, rather than waiting to be assigned work or relying on job specs.
- Push & pull context on your work rather than waiting for information from others and assuming people know what you’re doing.
- Communicate to be understood rather than pushing out information and expecting others to work to understand it.
- Stay a small team - misalignment and politics scale super-linearly with team size. Small protocol teams rival much larger traditional teams.
Rejection of mediocrity & high performance
- Give direct feedback to everyone immediately - rather than avoiding unpopularity, expecting things to improve naturally, or trading short-term pain for extreme long-term pain.
- Embrace an extreme learning rate - rather than assuming limits to your ability / knowledge.
- Don’t quit - push to the final outcome, despite any barriers.
- Be anti-fragile - balance short-term risk for long-term outcomes.
- Reject waste - guard the company’s time, rather than wasting it in meetings without clear purpose/focus, or bikeshedding.
- Build and design thinly.
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