Lead applied model development for computer vision and broader ML/data science use cases. Build, fine-tune, evaluate, and deploy models for object detection, segmentation, classification, video analysis, and time-series forecasting/anomaly detection. Account for real-world hardware constraints and deploy models to edge devices.
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Senior Computer Vision Engineer to own applied model development across computer vision, machine learning, and data science use cases — building and deploying solutions for object detection, image segmentation, classification, and video analysis. You will evaluate and fine-tune model architectures using PyTorch and TensorFlow, build broader ML models for forecasting and anomaly detection, and apply practical knowledge of computer vision hardware including cameras, sensors, and edge devices.
WHAT YOU WILL DO
- Own the applied model development process across computer vision, AI/ML, and broader data science use cases;
- Translate complex business problems into viable, practical, and scalable AI/ML solutions;
- Evaluate various model options, train and fine-tune selected architectures, and rigorously analyze model performance;
- Develop and deploy solutions for object detection, image segmentation, image classification, and video analysis;
- Build and maintain models for time-series forecasting, anomaly detection, regression, clustering, and general data analysis;
- Apply practical knowledge of real-world constraints—such as lighting, sensor limitations, and edge device compute power—to ensure optimal data quality and robust model performance in production.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 3 to 5 years of professional experience in Computer Vision, Machine Learning, Data Science, or a related field;
- Degree in Computer Science, Engineering, Data Science, Mathematics, or a related discipline (or equivalent practical experience);
- Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
- Strong, production-level proficiency in Python;
- Deep hands-on experience with PyTorch and/or TensorFlow;
- Proven track record of building and deploying models for detection, segmentation, classification, and image/video analysis;
- Solid understanding of broader ML and data science techniques (time-series modeling, forecasting, anomaly detection, regression, and clustering);
- Practical experience working with computer vision hardware, including cameras, sensors, and lighting setups;
- Familiarity with deploying models on edge devices;
- Strong understanding of how physical and real-world constraints impact data quality, model training, and inference;
- Upper-intermediate English level.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.
Meet Our Recruitment Process
Application → Coding Challenge → Video Interview → Technical Interview or Hiring Manager Interview
Each step helps us understand your skills and overall fit.
If it’s a match, you’ll receive an offer.
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
