Autonomy Engineer – Deep Learning

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Job Description

Autonomy Engineer – Deep Learning

Full-Time | Core Team

LAT Aerospace | Perception & Autonomy


At LAT Aerospace, we’re building India’s first clean-sheet hybrid-electric STOL aircraft and a next-generation autonomy stack powering aircraft for complex missions. Our team is kicking off a new chapter — developing the full flight-control, obstacle-avoidance, GNSS-denied navigation, and swarm-coordination layers that will define LAT’s autonomy architecture. As a Deep Learning Autonomy Engineer, you will build and deploy real-time neural models for object classification, scene understanding, semantic threat identification, and perception-assisted navigation.


What you’ll do?

  • Design and train deep learning models for object classification, detection, semantic segmentation, threat identification, and multi-class scene understanding from aerial camera feeds.
  • Apply LLMs and multimodal AI models for contextual reasoning on image data — assisting in early threat classification, prioritization, and mission-level decision support.
  • Develop lightweight, real-time inference pipelines optimized for edge devices and constrained compute aboard UAVs.
  • Build data-processing workflows for mining, curation, labeling, and augmentation from large volumes of real flight data.
  • Use synthetic datasets, domain randomization, and simulation environments to accelerate training and improve model generalization.
  • Integrate deep vision models with the autonomy pipeline: navigation, obstacle avoidance, swarm behavior, and mission control.
  • Optimize models for latency, throughput, memory efficiency, and robustness under diverse lighting, motion, and environmental conditions.
  • Create evaluation benchmarks and metrics to measure classification accuracy, threat-detection reliability, and real-time inference performance.


What we're looking for?

  • Strong experience designing and training deep learning models for image/video tasks — classification, detection, segmentation, or tracking.
  • Proficiency with PyTorch (preferred) or TensorFlow for model development.
  • Ability to write clean, structured Python code; some C++ experience is a plus.
  • Familiarity with CNNs, Vision Transformers, multimodal models, and modern architectures used in perception.
  • Understanding of real-time deep learning constraints on embedded Linux systems.
  • M.S. or Ph.D. in computer science, electrical engineering or related discipline


Why LAT?

  • Core-team role building the autonomy brain of India’s most ambitious aerospace startup.
  • Ownership, speed, and the opportunity to define a new class of systems from scratch.


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