L
Lodestar
Software Engineer (Perception)
Skills
Google Cloud PlatformDeep LearningDockerPythonMachine LearningAIAWSLinuxKubernetesAzure
1 month ago
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Important information
Contract type:
Permanent
Salary:
$99,000 – $174,000 / year
Location:
Los Angeles, CA, USA
Work mode:
Onsite
Published on:
19 September 2026
What they need
- As a Software Engineer I - Perception at Lodestar, you’ll be joining the perception and machine vision teams to rapidly grow our vision and perception models at MITHRIL’s center
- You’ll help build and refine algorithms that detect, classify and understand unknown space targets in real time
- Working alongside senior perception engineers, you’ll combine computer vision, image processing and machine learning to develop the custom models that underpin autonomous decision-making in complex and uncertain space environments
- This is an early-career role
- We’re looking for strong fundamentals and fast learning rather than a long track record, and you’ll be given real ownership early with the support to grow into it
- We proudly have an “extreme ownership” oriented engineering culture
- Contribute to the perception system at the core of Lodestar’s autonomy software suite
- Work through the full lifecycle of perception algorithms alongside senior engineers including literature review, training, evaluation, optimisation and deployment
- Build on and optimise our existing models for edge computing, and develop new components with guidance from the perception leads
- Help develop and test our methods for predicting the relative pose of dynamic space targets in harsh and unpredictable visual environments
- Integrate perception models into mission simulation environments and real-time autonomy pipelines
- Contribute to the design of realistic sensor models and digital twins to improve perception fidelity in mission scenarios
- Maintain and extend our perception tooling, model training infrastructure, and evaluation frameworks
- Collaborate across the autonomy, estimation, and mission software teams to support perception fidelity, performance, and scalability- Solid software engineering skills in Python, and working proficiency in C++
- Foundational DNN/ML knowledge and hands-on experience with computer vision or image processing libraries (e.g. OpenCV)
- Demonstrated ability to take an ML model from training through to evaluation, in any setting — coursework, research, or industry
- 0–2 years of professional experience in machine learning, robotics, computer vision, or a related field. Internships, research placements, and substantial academic or personal projects all count
- Bachelor’s or Master’s degree in AI/ML, Computer Science, Robotics, a related field, or equivalent experience
- Experience developing or deploying ML models to real-time or resource-constrained systems
- Broad understanding of modern perception systems and their architecture
- Exposure to sensor measurements from RADAR, electro-optical sensors, RF sensors, or LIDAR
- Familiarity with image processing techniques (e.g. feature extraction, segmentation, filtering, stereo matching) to support 3D reconstruction and target classification
- Experience optimising neural networks or geometric algorithms using CUDA kernels, TensorRT, or other GPU acceleration frameworks
- Exposure to distributed training or cloud-based scaling of ML models (AWS, GCP, or Azure)
- Experience with Linux, Git, and CI/CD pipelines
- Understanding of networking and communication protocols for distributed autonomy systems
- Comfortable with containerisation tools such as Docker and Kubernetes
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