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Job Description: Staff Machine Learning Engineer
Fruition Group · United States (Remote)

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Meet the hiring team

James Reynolds  
 3rd
Practice Lead| Autonomy & Embedded Systems | Permanent & Contract Hires across USA
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About the job
Staff Machine Learning Engineer, Perception



Overview :

We are seeking a Staff Machine Learning Engineer to lead the development, training, and deployment of advanced perception models that power real-time understanding of the autonomous vehicle’s environment. You will drive innovation in object detection, tracking, 3D scene understanding, and multimodal fusion while defining the ML architecture that delivers high-accuracy, production-grade perception across diverse driving domains. This role combines hands-on model development with cross-functional technical leadership and mentorship.


Responsibilities :

Lead development of state-of-the-art perception models (detection, tracking, segmentation, 3D geometry, occupancy modeling, sensor fusion).
Architect scalable ML systems for large-scale training, fleet-driven data pipelines, and real-time inference on AV compute hardware.
Optimize neural networks using quantization, pruning, distillation, TensorRT, CUDA, and hardware-specific acceleration for onboard deployment.
Define and own perception KPIs—accuracy, latency, robustness, calibration, failure modes.
Build and maintain data pipelines integrating fleet-loop learning, auto-labeling, synthetic augmentation, and continuous evaluation.
Collaborate closely with mapping, prediction, planning, hardware, and platform teams to integrate perception into the full autonomy stack.
Mentor ML/CV engineers on model design, best practices, and research-to-production transitions.
Drive the maturation of research prototypes into reliable, safety-critical AV systems.


Qualifications: 

B.S or M.S. or Ph.D. in computer science, or a related field. 
6+ years of experience delivering ML perception systems for autonomous driving, or robotics based products. 
Strong expertise with PyTorch and TensorFlow; strong fundamentals in computer vision and deep learning.
Experience in key domains such as detection, tracking, segmentation, geometric vision, multi-sensor fusion (camera, LiDAR, radar), or 3D spatial reasoning.
Demonstrated experience deploying ML models on real-time edge compute (GPU, TPU, specialized accelerators).
Strong software engineering skills in Python or C++, and familiarity with ROS2, CUDA, and high-performance inference frameworks.
Experience with large-scale data processing and orchestration (Airflow, Spark, Kafka, Ray).
Proven technical leadership and mentorship experience.
Publications or patents in autonomous driving, perception, or ML research are a plus.

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