About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Engineering.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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Overview

This is an entry-level Perception Software Engineer role (New Grad) supporting space-domain autonomy at a confidential client. The position is a 3‑month temporary engagement with potential to convert to regular employment based on performance and business need. Work focuses on hybrid perception systems that combine classical computer vision and modern deep learning to enable autonomous spacecraft detection, tracking, classification, and navigation.

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What You’ll Do

You will implement, test, and deploy perception algorithms across the full stack — from synthetic data generation and neural network training to classical tracking, coordinate transforms, and embedded inference on edge hardware.

• Implement classical tracking and state estimation (Extended Kalman Filters, data association, track management)
• Train and validate neural networks for detection and classification (e.g., YOLO, ResNet variants) using PyTorch
• Build hybrid perception pipelines: detection → association → tracking → coordinate transforms → angle-only measurements for navigation
• Develop image processing routines: hot-pixel filtering, adaptive thresholding, centroiding, connected component analysis, star catalog matching
• Generate synthetic training datasets (Blender/unreal + domain randomization) for rare/edge scenarios
• Optimize and deploy models to edge hardware (quantization, ONNX Runtime, TensorRT, INT8/FP16 workflows) and integrate with C++ inference engines
• Validate system performance with software-in-the-loop, processor-in-the-loop, and hardware-in-the-loop testing

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Responsibilities

• Design and implement Extended Kalman Filters and multi-object tracking pipelines (Hungarian algorithm, track life-cycle management)
• Train detection and classification models; produce reproducible training pipelines and evaluation metrics
• Develop robust coordinate transformation chains (pixel → camera → body → ECI) accounting for lens distortion and attitude uncertainty
• Produce production-quality C++ flight code and Python tooling for training and evaluation
• Perform debugging and numerical stability analysis; tune covariances and failure-mode mitigations
• Collaborate with teams to integrate perception outputs into navigation and mission software

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Minimum Qualifications

• Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field
• Coursework or practical experience in computer vision and estimation theory (or strong willingness to learn both)
• Proficiency in Python; some experience or coursework in C++
• Familiarity with either classical tracking (Kalman filters, data association) OR deep learning model training (PyTorch)
• Good understanding of linear algebra, probability, and coordinate transformations
• Strong debugging skills and ability to implement algorithms from research literature
• U.S. Citizen (required for facility access and government contracts)

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Preferred Skills & Experience

• Prior experience with Extended Kalman Filters, multi-object tracking, or state estimation
• Hands-on experience training detection/classification networks (YOLO, Faster R-CNN, ResNet) in PyTorch or TensorFlow
• Knowledge of camera intrinsics/extrinsics, quaternions, rotation matrices, and orbital frames (ECI, LVLH/RIC)
• Experience with model optimization and edge deployment (quantization, ONNX, TensorRT, INT8/FP16)
• Familiarity with OpenCV and classical image-processing pipelines
• Experience generating synthetic datasets (Blender, Unreal) and applying domain randomization
• Prior project or internship deploying algorithms to embedded systems (NVIDIA Jetson, ROS, mobile platforms)
• Experience debugging perception systems (false positives, missed detections, ID switching)

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Compensation

• For candidates in Colorado (posted location area): Base salary approximately $75,000 per year.
• For candidates in Long Beach, CA: Base salary approximately $80,000 per year.

Actual pay may vary based on relevant experience, education, and location. Because this posting is for a role in Colorado, the Colorado salary figure above is provided to comply with applicable pay transparency requirements.

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Work Location & Other Requirements

• Worksite: Candidates should be located near Centennial, CO or Long Beach, CA; the authoritative posting location is Federal Heights, CO.
• This role may require on-site facility access and participation in government contract work; to conform to U.S. Government space technology export regulations (including ITAR), you must be a U.S. citizen, lawful permanent resident, protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain required authorizations from the U.S. Department of State.
• Physical demands and work environment: the role may involve typical lab/office conditions and occasional hardware testing that could include variable temperature, noise, and standing or lifting during integration/testing.
• Employment type: temporary 3‑month engagement with potential conversion; work is expected to be full-time during the engagement.

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Confidential Client Statement

This role is being hired on behalf of a confidential client. All references to the employer in this posting have been replaced with “Confidential Client” to protect the client’s identity during this recruiting process.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.