Symbolica is looking to bridge the gap between theoretical mathematics and cutting-edge technologies by creating symbolic reasoning models that think like humans. The company aims to transform industries by empowering machines to solve complex challenges with precision and insight, moving beyond traditional data-hungry neural networks to focus on the structures of thought.
Requirements
- 5+ years of hands-on software engineering experience
- Proven ability to execute on incomplete specs and drive projects to completion
- Strong experience writing production-quality code (Python & Rust strongly preferred)
- Comfortable building full-stack systems (APIs, data pipelines, microservices, internal tools)
- High standards for code quality, maintainability, and correctness
- Comfortable in fast-moving, ambiguous environments where priorities shift quickly
- Experience supporting ML research or building ML infrastructure is a plus
Responsibilities
- Translate research prototypes and high-level concepts into production-quality software
- Own deliverables end-to-end: take specifications, clarify requirements, and execute to completion
- Build systems that are correct, reliable, maintainable, and performant
- Work closely with ML researchers and engineers to integrate research outputs into functional systems
- Own critical engineering tasks with high standards and attention to detail — data pipelines, API integrations, testing, error handling, system integration, and more
- Participate in code reviews, technical discussions, and architecture planning
- Contribute to improving processes for how we build, ship, and deliver features across teams
Other
- Take full ownership of delivering working systems from prototypes and high-level specs
- Take ideas from the research team, turning them into production-quality systems, and shipping them quickly
- Work closely with researchers, ML engineers, and leadership to turn ambitious ideas into real products
- Be expected to move fast, handle ambiguity, and fill the critical execution gap between research and production
- Thrives on shipping — who sees incomplete specs as an opportunity, not a blocker — and who wants to build systems that work reliably, at scale, and in the real world
- Bias for ownership: you see what needs to get done and take responsibility for delivering
- Symbolica is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, or sexual orientation.
