Chief Architect / R&D Researcher (вакансія неактивна)

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 Responsibilities

Architecture & 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.