Software Engineer - Simulation Infrastructure
🌉 San Francisco, CA (On-site)
About Us
Softmax develops multi-agent reinforcement learning simulations focused on social learning scenarios. Our work explores how multiple agents can maintain individual identity while achieving coherence as a unified system—similar to multicellularity in nature.
The Role
We’re seeking a software engineer to build and enhance our experimental infrastructure. You’ll work on critical systems that enable our research, focusing on scalability, flexibility, and functionality.
Key Responsibilities
- Design and implement batch processing systems for reinforcement learning training
- Enhance our simulator environments with new features and capabilities
- Build visualization tools and evaluation frameworks for complex agent interactions
- Collaborate with researchers to translate experimental needs into technical implementations
- Optimize systems for performance and scale
Requirements
- Strong software engineering background with demonstrated experience building complex systems
- Proficiency in designing and implementing scalable infrastructure
- Experience with distributed computing and batch processing systems
- Ability to work collaboratively in a research-oriented environment
- Interest in multi-agent systems and emergent behavior
Nice to Have
- Familiarity with reinforcement learning concepts
- Experience with simulation environments
- Background in visualization of complex data
- Prior work with cloud infrastructure for ML workloads
Company Culture
Our team values coherence, both in our technical work and our approach to collaboration. Many team members have backgrounds in practices that cultivate insight (meditation, contemplative practices, etc.), though this is not a requirement. We appreciate candidates who are thoughtful about systems — both technical and social.
Compensation
Salary between $150,000 to $300,000 per year, plus equity compensation.
