About Ndea

Building AGI that can innovate.

Tech description:

# Deep Learning / Search Guidance Current deep learning-based AI, while impressive and economically valuable, is ultimately constrained by its inability to efficiently learn and adapt. It excels at known tasks but crumbles when faced with open-ended problems. It reflects back to us only the knowledge, programs, and abstractions found in its training data. Like the man behind the curtain in The Wizard of Oz, it hides the fact that human general intelligence created the training data. If AI cannot efficiently adapt, it is forever constrained by what humans teach it. To compress the next 100 years of scientific progress into 50, or perhaps 10, we need general intelligence, not task-specific skill. We need computers that can pose problems and explore new territory, not just apply known solutions. We need computers that can innovate. The path to AGI is not through incremental improvements to existing methods. The problems with deep learning are fundamental and cannot be addressed superficially. It's time for a new paradigm. The good news is that we know what it is: program synthesis. # Program Synthesis / Symbolic Reasoning We believe program synthesis holds the key to unlocking AGI. Instead of interpolating between data points in a continuous embedding space, program synthesis searches for discrete programs, or models, that perfectly explain observed data. This allows it to achieve much greater generalization power with extreme data-efficiency, requiring only a few examples to learn. By leveraging deep learning to guide program search, we can overcome the computational bottlenecks of program synthesis. This fusion integrates intuitive pattern recognition with rigorous reasoning, enabling autonomous abstraction and skill acquisition from minimal data. Compared to deep learning, program synthesis is a much less mature research field. The state of program synthesis in 2025 looks a lot like deep learning circa 2012. But we are not alone in recognizing the potential of program synthesis — it's a technique every frontier AI lab is now starting to explore. Most, however, believe it's only a small component of what's needed for AGI. We believe program synthesis and deep learning are equally important. We are at the crest of a pivotal moment in scientific history and the world deserves every possible direct, unique attempt to build AGI.

Job description:

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 high-ownership role for someone who wants to operate at the leading edge of neuro-symbolic AI, designing, implementing, and validating new approaches in code. We offer: * Meaningful equity, competitive salary, and benefits * Aggressive compute budget * Small, high-talent-density, globally remote team (work from any country) Qualifications: * Strong hands-on experience building and debugging RL or search-driven learning systems * Research contributions in reinforcement learning, planning, or search (papers and/or industry work) * Evidence of turning research ideas into working implementations * Comfort operating as an individual contributor in a small, high-agency environment * Interest in symbolic approaches (program synthesis, logic, solvers, formal methods, etc.) * Clear communication and documentation skills for complex research/engineering workflows Nice-to-have: * Experience with search-guided learning in structured or combinatorial domains * Work in planning-heavy, exploration-heavy, or solver-adjacent settings * Familiarity with discrete mathematics, verification, or theorem-proving style problems This role may not be a fit if you’re primarily focused on… * LLM-only RLHF or post-training pipelines * World model scaling or agent abstraction layers as the main artifact _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._

Skills:

Python, Deep Learning, Reinforcement learning (RL)

Ndea remote jobs

Technical Staff - Search Guidance