Autonomy (MLOps) - Software Engineer at Delian Alliance Industries

Overview

We are seeking a Software Engineer for our Autonomy team with a focus on real-time detection systems. In this role, you’ll develop core components of the perception stack that allow our autonomous systems to detect, classify, and track objects across varied environments. You’ll work with perception and sensor integration teams to deliver reliable detection pipelines for deployment in the real world. This role is ideal for engineers who enjoy solving vision and sensor-fusion challenges at the core of autonomous perception.

In this role you will get to

• Develop detection pipelines for real-time inference using sensor modalities such as cameras and radars.
• Integrate and optimize deep learning models (e.g., 2D/3D object detection, segmentation) for deployment on embedded platforms.
• Build robust, scalable perception systems capable of operating under variable lighting, weather, and scene complexity.
• Collaborate with tracking, planning, and calibration teams to ensure consistent handoff of perceptual data throughout the autonomy stack.
• Contribute to tools and infrastructure for performance analysis, dataset creation, labeling, and model evaluation.

Must have experience

• Strong programming skills in Python and C++, especially for high-performance robotics or real-time applications.
• Experience implementing or integrating object detection and/or semantic segmentation models in production environments.
• Familiarity with machine learning frameworks such as PyTorch or TensorFlow, and knowledge of model training/inference workflows.
• Proficiency with NVIDIA’s edge computing stack, including CUDA, TensorRT, DeepStream SDK for real-time multi-stream video analytics and pipeline integration.
• Understanding of 3D geometry and computer vision fundamentals (e.g., projections, point cloud processing, depth estimation).
• Experience working with multi-modal sensor data (camera, LiDAR, radar) in perception pipelines.
• Ability to diagnose system-level failures and improve detection reliability across varied operational conditions.

Nice To Have Experience

• Experience deploying and optimizing perception models on NVIDIA Jetson (e.g., Xavier, Orin) or similar embedded platforms.
• Familiarity with ROS/ROS2 and integrating detection nodes into larger autonomy frameworks.
• Understanding of sensor calibration, data association, and perception uncertainty modeling.
• Experience with active learning, dataset bootstrapping, or labeling tools and pipelines.
• Contributions to open-source projects in robotics, computer vision, or ML infrastructure.

Seniority level

• Entry level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Defense and Space Manufacturing

Offices: Athens and London.