Machine Learning Engineer, Perception & Computer Vision
Overview
Agtonomy seeks a Machine Learning Engineer to build perception systems for autonomous heavy machinery in agriculture and turf. You'll own real-time Computer Vision and LiDAR fusion, enabling safe operation in dusty, occluded, and unstructured environments. Collaborate with a small team of engineers and industry experts, shipping models from research to embedded hardware. This role drives the shift from bounding boxes to dense scene understanding and foundation-model-driven data engines.
What You'll Do6
- 1Develop real-time perception models for open-world obstacle and terrain understanding using PyTorch and TensorFlow.
- 2Build multi-modal fusion that combines camera and LiDAR into a unified 3D/BEV representation, robust to occlusions and sensor degradation.
- 3Optimize models for low-latency inference on resource-constrained hardware, balancing accuracy and performance with TensorRT and quantization.
- 4Design auto-labeling pipelines that use foundation models and teacher-student distillation to scale labeling and close the loop from field interventions.
- 5Design data and evaluation pipelines that curate large multi-sensor datasets and surface failures fast with strong visualization and debugging tooling.
- 6Analyze performance metrics and iterate on algorithms to improve accuracy (mAP, IoU) and efficiency of perception subsystems.
Requirements8
- 1MS/PhD in Computer Science, AI, or related field, or 6+ years of industry experience building vision-based perception systems.
- 2Deep expertise in modern perception models: detection, segmentation, mono/stereo/metric depth, BEV/occupancy, sensor fusion, and 3D scene understanding.
- 3Fluency adapting, fine-tuning, and distilling large pre-trained vision and vision-language models.
- 4Strong grounding in multi-sensor integration: camera, LiDAR, radar, calibration, spatiotemporal sync, and cross-modal fusion.
- 5Experience handling large datasets efficiently for labeling, training, and evaluation.
- 6Fluency in Python with PyTorch, TensorFlow, OpenCV and ability to write production-ready code for real-time systems.
- 7Proven ability to design experiments, analyze metrics (mAP, IoU, latency/throughput, calibration/ECE), and optimize to meet safety requirements.
- 8Eagerness to work hands-on in a collaborative small team with high ownership.
Salary Insight
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