Lead Software Engineer, Computer Vision & Machine Learning
DroneDeploy
Software Engineering
Austin, TX, USA
Posted on Aug 31, 2024
Team Overview
We are a team of highly skilled developers working on an industry-leading photogrammetry platform used by customers worldwide.
Role Overview
We are seeking an experienced Machine Learning Engineer to join our Computer Vision team. We are a small team of highly skilled developers working on an industry-leading photogrammetry platform used by companies all around the world. Our customers have mapped over 150M acres from over 180 countries around the world, relying on our industry-leading speed, quality and accuracy to drive high ROI decisions in industries as diverse as construction, agriculture, mining, conservation, forestry, and infrastructure inspection.
Your work will leverage recent cutting edge advancements in machine learning to revolutionize our photogrammetry platform. In this role, you will lead the design, development, implementation and improvement of innovative machine learning models to solve 3D computer vision problems. This is a hands-on leadership role that requires a deep understanding of both machine learning and 3D computer vision.
Work Environment
- This is a fully remote position within the U.S., offering you the flexibility to design your workday to maximize productivity and balance. We provide you with the autonomy to work in a way that suits you best as long as you’re able to collaborate effectively with our team, particularly during Pacific Time zone business hours.
- While our team is distributed across the country, we believe in the power of face-to-face connections. You'll have the opportunity to meet with colleagues in person at least once a year, fostering deeper collaboration and camaraderie. These occasional in-person meetings will be scheduled with plenty of advance notice, and we'll cover all travel expenses, making sure you’re comfortable and prepared.
- In addition to a competitive salary, we offer comprehensive health benefits, flexible time away from work, and support for ongoing professional development. We prioritize your well-being and personal growth as much as your professional success.
Responsibilities
- Train, improve, evaluate, integrate and deploy machine learning models for a variety of computer vision use cases such as: feature detection/matching, place recognition, structure from motion, depth estimation and completion, mesh reconstruction, point cloud filtering, NeRFs, gaussian splats.
- Optimize the performance of ML systems for speed, accuracy, and efficiency.
- Take ownership of deliverables from design, implementation, release, and support as a self-driven engineer. Be willing to pick up whatever knowledge you're missing to get the job done.
- Stay up-to-date with the latest 3D ML and vision advancements and evaluate their potential application to our workflows.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field with 5+ years of professional experience in 3D Machine Learning and Computer Vision
- Experience designing, building, integrating, deploying, debugging and maintaining large-scale production 3D computer vision systems.
- Ability to timebox experiments, iterate effectively and leverage excellent problem-solving skills to triage routes to success.
- Experience training and improving models for feature detection/matching, depth estimation or mesh reconstruction
- Experience with modern ML in Pytorch, Keras, TensorFlow or equivalent
- Experience building and improving models like Mask2former, MaskRCNN, Resnet, Unet
- Experience with CI/CD tools (e.g., Jenkins, GitHub CI)
- Experience as effective remote employee able to overlap standup AM meetings PST
- Strong communication and leadership skills.
Preferred Qualifications & Expertise
- Proficiency in developing and debugging C++
- Experience running and monitoring multiple ML experiments in cloud environments concurrently.
- High degree of comfort with training and inference on cloud instances cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
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