Technical Staff - Symbolic Reasoning

Location: Remote
Type: Full-time

Ndea is building AGI systems that depend on search guidance. We're hiring hands-on researchers/engineers to drive our deep learning effort in search guidance, training models to make structured search more efficient and reliable.

This is a build-focused role at the leading edge of neuro-symbolic AI, building the symbolic foundations that make learned systems precise, interpretable, and scalable.

We offer:
  • Meaningful equity, competitive salary, and benefits
  • Aggressive compute budget
  • Small, high-talent-density, globally remote team

Ndea is an equal opportunity employer and does not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or any other legally protected status.

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Apply

If you're interested in this role, send us an email including the following items to: future@ndea.com

  • Your location (city, country)
  • Something impressive thing you've created or published, ideally in the program synthesis or symbolic space
  • Links to your profile(s) (e.g., Google Scholar, GitHub, X, LinkedIn, etc.)
  • Your resume (optional if the above links are sufficient)

Refer

Know someone who might be a good fit for this role? Refer them to us, and if they're hired and stay for 30 days, you could earn a $10,000 bonus.

Learn more

Qualifications:
  • Strong direct experience building and debugging symbolic systems
  • Research contributions in program synthesis, formal methods, automated reasoning, or related areas (papers and/or industry work)
  • Strong Python engineering skills
  • Familiarity with search algorithms (MCTS, best-first, heuristic search) and how to integrate policy guidance
  • Comfort working with data pipelines and evaluation for program synthesis or structured prediction tasks
  • Clear communication and documentation skills for complex research/engineering workflows
Nice-to-have:
  • Experience with program synthesis, inductive logic programming, proof search, or solver-guided program generation
  • Familiarity with programming language semantics