Professional Resume Template for

Computer Vision Engineer

Elena R. Sterling

Seattle, WA

(206) 555-0143

elena.sterling@email.com

linkedin.com/in/elena-sterling | github.com/elenasterling | elenasterling.dev

Professional Summary

Pragmatic Computer Vision Engineer with a 5-year track record of designing, training, and deploying deep learning models for real-time object detection and spatial mapping. Expertise includes optimizing inference latency on embedded GPU architectures, implementing MLOps pipelines, and training custom convolutional neural networks (CNNs) and vision transformers (ViTs). Successfully reduced model inference latency by 34% using TensorRT quantization and improved detection accuracy by 15% on edge devices. Proficient with PyTorch, OpenCV, CUDA, TensorRT, Docker, and AWS SageMaker.

Work Experience

Computer Vision Engineer — Aether Vision Systems

Seattle, WA | June 2023 – Present

  • Engineered and deployed a real-time object detection system using YOLOv8 on NVIDIA Jetson devices, reducing latency by 38% while maintaining a 94.2% mean Average Precision (mAP).
  • Optimized PyTorch model architectures via PyTorch TensorRT quantization (FP16/INT8), decreasing edge inference energy consumption by 24%.
  • Designed automated MLOps pipelines using AWS SageMaker and Docker to process 2.5 million daily images, accelerating model retraining cycles by 40%.
  • Developed custom dataset curation tools that filtered out 15% of redundant frames, reducing data labeling costs by $45,000 annually.

Machine Learning Engineer — Spectra Autonomous Systems

San Francisco, CA | July 2021 – May 2023

  • Built an automated video segmentation pipeline using PyTorch and OpenCV for autonomous navigation, improving classification accuracy by 11%.
  • Fine-tuned deep learning models on a cluster of 32 GPUs, reducing training time from 72 hours to 48 hours via distributed training.
  • Implemented robust regression models for spatial depth estimation, reducing distance calculation error rate by 18%.
  • Collaborated with product teams to integrate computer vision APIs into 3 core products, increasing user engagement by 14% across 85,000 active devices.

Education

Bachelor of Science in Computer Science

Cascade Institute of Technology · Seattle, WA · 2021

Skills

PyTorch, TensorFlow, OpenCV, CUDA, TensorRT, Python, C++, Docker, Kubernetes, AWS SageMaker, Git, MLOps, Image segmentation, Object detection, Vision Transformers (ViTs), CNNs, Supervised learning

Projects

Real-Time Edge Segmentation Engine

Role: Lead CV Engineer

Tools: PyTorch, OpenCV, TensorRT, Jetson Orin

Optimized a semantic segmentation network for autonomous warehouse robots, reducing processing latency from 65ms to 32ms and enabling obstacle detection at 30 FPS.

Synthetic Data Generation Pipeline

Role: Machine Learning Engineer

Tools: Stable Diffusion, Blender, Python, Docker

Built a synthetic image generation tool that created 120,000 photorealistic training samples, boosting model generalizability and reducing physical dataset collection time by 5 weeks.

Certifications

  • Google Cloud Certified Professional Machine Learning Engineer (2024)
  • NVIDIA Deep Learning Institute - Edge AI on Jetson (2022)

Additional information

  • Languages: English (Native), German (Conversational)
  • Volunteer Work: Technical mentor for high school robotics teams at local community centers (2022-present)
  • Availability: 2 weeks notice

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Job Market Insights

Market data and opportunities for

Computer Vision Engineer

Job Market Insights

$120,000

-

$175,000

Avg:

$148,000

Growth Outlook:

The demand for Computer Vision and Machine Learning Engineers is experiencing high growth in the United States, driven by advancements in autonomous systems, robotics, medical diagnostics, and spatial computing. As visual data continues to expand, industries require engineers who can build, optimize, and deploy intelligent visual models onto edge and cloud devices. Employment for related occupations like computer and information research scientists is projected to grow by 22% over the next decade.

22% growth over 10 years

Key Skills Required

Focus on these skills when customizing your resume for recruiter screenings.

Solid understanding of deep learning frameworks like PyTorch and TensorFlow for building custom CNNs and ViTs || Hands-on experience optimizing models for deployment using TensorRT, ONNX, and OpenCV || Proficiency in Python and C++ for implementing production-ready computer vision pipelines

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Computer Vision Engineer

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FAQ

Common questions about the

Computer Vision Engineer

position

What programming languages are most important for a Computer Vision Engineer?
What is the difference between PyTorch and TensorFlow in computer vision workflows?
How do you optimize computer vision models for edge devices?
Is a Ph.D. required to work as a Computer Vision Engineer?
What is mean Average Precision (mAP) in object detection?
How is generative AI impacting computer vision?
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