Supports large-scale AI workflows involving image and video dataset curation, annotation management, model training, evaluation, benchmarking, documentation, and failure-case analysis. The role collaborates with senior engineers to improve data and algorithms while developing foundational experience in applied modeling or MLOps.
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 Junior/Middle Computer Vision Engineer to support high-volume execution across data preparation, model training, and evaluation for an AI team working with large-scale image and video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role offers a a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.
WHAT YOU WILL DO
- Curate large-scale image and video datasets, manage labeling processes and workflows, and ensure the highest standards for dataset quality;
- Run model training and evaluation jobs, ensuring experiments are executed smoothly and efficiently;
- Document training results, maintain ongoing evaluation benchmarks, and track model performance over time;
- Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement;
- Take ownership of foundational tasks that support the broader team’s AI/ML lifecycle, directly contributing to the speed and success of production deployments.
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;
- 1 to 3 years of experience in software engineering, data science, machine learning, or a related field;
- Degree in Computer Science, Data Science, Engineering, 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);
- Foundational coding skills in Python;
- Foundational understanding of machine learning concepts and workflows;
- Basic knowledge of computer vision principles (e.g., image processing, object detection basics);
- Basic familiarity with cloud environments and compute resources;
- A strong, demonstrable willingness to learn and adapt in a fast-paced, mentorship-driven environment;
- Excellent attention to detail, specifically regarding data quality and documentation;
- 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.
Similar Jobs
Software
Supports AI/ML workflows involving large-scale image and video datasets. Responsibilities include curating datasets, managing annotation workflows, running model training and evaluation jobs, maintaining benchmarks, documenting results, tracking model performance, and analyzing failure cases with senior engineers. The role offers growth toward applied modeling or MLOps and requires foundational Python, machine learning, computer vision, cloud, and data-quality skills.
Top Skills:
Cloud ComputingComputer VisionImage ProcessingMachine LearningObject DetectionPython
Financial Services
Supports client onboarding and product implementation for treasury and banking solutions. Executes routine and semi-routine implementation activities, resolves standard queries, escalates unusual issues, analyzes data for insights, and builds trust with clients and stakeholders. The role also contributes to strategic projects, communicates onboarding procedures, and supports timely transitions to the Chase banking platform.
Financial Services
Leads enterprise-scale Microsoft Hyper-V infrastructure engineering across global data centers. Designs resilient clusters, automates provisioning and compliance with PowerShell and DSC, develops C#/.NET orchestration services, benchmarks performance, troubleshoots full-stack infrastructure issues, evaluates server hardware, remediates vulnerabilities, documents architectures, and mentors engineers. The role also promotes validated, auditable use of enterprise AI capabilities in infrastructure operations.
Top Skills:
.Net 8Amd EpycAnsibleAutomated TestingC#Ci/CdDesired State Configuration (Dsc)DiskspdElbenchoFioGpuIntel XeonKvmLoad BalancingMicrosoft Hyper-VMicrosoft System Center VmmNvmePlatform ApisPowershellQualysS2DSccmScomSdnSetVlansVmfleetVmware EsxiVswitchWsfc
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

