The Fourth Law / TFL / Четвертий Закон is an autonomous robotics company focused on solving massively scalable autonomy for defensive FPV drones. The company has offices in the US, EU, and Ukraine and is on a mission to increase the defensive capabilities of the Free World. Its name is a reference to Isaac Asimov’s three laws of robotics and the search for an enigmatic Fourth Law. The role We’re hiring a Chief Architect / R&D Researcher to lead the technical architecture and research direction for our autonomy stack—bridging applied ML/computer vision, real-time robotics, and systems engineering. This is a senior, high-impact role for someone who can do deep technical work, design scalable architectures, and help multiple teams move faster with clear technical choices.
You’ll operate as a force multiplier across R&D: defining how components fit together, how we test and validate in simulation and in real-world conditions, and what research bets we should make next. Key ResponsibilitiesArchitecture & technical strategy * Own end-to-end architecture for autonomy modules: sensing → perception → tracking → decision/control → deployment. * Define system interfaces, data flows, latency budgets, and reliability requirements for real-time applications. * Drive technology roadmap: evaluate build vs buy, research vs productization, and trade-offs across accuracy, compute, and robustness.
Applied research & prototyping * Lead applied research in computer vision / ML for real-world, noisy, fast-moving scenarios (object detection, segmentation, tracking, self-/weak supervision, domain adaptation). * Prototype and de-risk new methods; turn research results into deployable, measurable improvements. * Own the “research pipeline”: datasets, labeling strategy, training/eval protocols, reproducibility, and model lifecycle.
Performance, deployment & optimization * Optimize models and pipelines for real-time constraints (GPU/CPU/NPU): quantization, pruning, compilation, acceleration. * Collaborate on embedded/edge deployment (C++/Python components, OpenCV, PyTorch/TensorFlow toolchains, inference runtimes). * Set standards for performance tuning and benchmarking (latency, throughput, power, memory).
Validation, simulation & field feedback loop * Define evaluation methodology across simulation and real-world tests: metrics, test suites, failure taxonomy, regression checks. * Build tight feedback loops from deployments: collect edge cases, design experiments, prioritize fixes. * Ensure strong documentation of architecture decisions, experiments, and technical specifications.
Cross-team technical leadership * Partner with engineering/product leadership to align research priorities with product needs. * Mentor senior engineers/researchers; raise technical bar through reviews, design docs, and technical forums. * Help build a culture of rigorous experimentation and fast iteration.
Required Skills & Experience * 8+ years of experience in computer vision / ML / robotics / autonomy (or similar applied R&D), with proven impact on shipped systems. * Strong understanding of CV techniques: detection, segmentation, tracking, geometric vision, and model evaluation. * Proficiency with modern ML stacks: PyTorch and/or TensorFlow, plus OpenCV. * Excellent engineering ability in Python and C++ (or equivalent), including production-quality code and performance debugging. * Experience with large datasets, GPU computing, and real-time system integration. * Strong systems thinking: can design architectures and interfaces that multiple teams can build on. * Clear technical communication: can write design docs, present trade-offs, and align stakeholders.
Nice to Have * Background in robotics/autonomy stacks (sensor fusion, state estimation, control loops). * Experience deploying on edge hardware. * Experience with simulation environments and synthetic data generation. * Familiarity with safety/reliability engineering and adversarial / robustness testing. * Publications, patents, or notable open-source contributions in related areas.
We Offer * Self-development and assistance. * Market salary. * Flexible/hybrid working hours. * 24 paid days off per year + 14 additional days off for veterans.
