Applied AI Research Engineer

About EAIGLEEAIGLE is an end-to-end AI platform transforming operations in the supply chain and logistics sectors through intelligent video and sensor data.
Our solutions are trusted by major logistics operators to optimize yard operations, automate vehicle access control, and enhance asset visibility - enhancing both security and operational efficiency at scale.
By leveraging cutting-edge computer vision and real-time data processing, we enable enterprises to drive efficiency and resilience at scale.
At EAIGLE, we're on a mission to bring AI-powered automation to the physical world, one yard at a time.We're hiring across multiple levels - if you're passionate about applied AI and ready to build systems that make an impact in the real world, we'd love to hear from you.About the RoleWe are looking for an Applied Computer Vision & ML Engineer to join our growing R&D team.
In this role, you'll help design, implement, and deploy machine learning and computer vision models that power EAIGLE's real-time video intelligence systems.
You'll work on practical and high-impact problems, from object detection and tracking to OCR and real-time model optimization for edge deployment.
You'll have access to large-scale sensor and video datasets, a robust in-house compute infrastructure, and the opportunity to work closely with senior researchers and engineers in a collaborative, high-ownership environment.
We're especially excited about candidates who are curious about the future of AI-powered perception - including recent advances in foundational vision and vision-language models (VLMs) - and how these can be adapted for practical, industrial applications.What you'll do Contribute to the design, training, and deployment of AI models for vision tasks such as:
Object detection, classification, OCR/text recognition Multi-camera tracking and vehicle behavior understanding Write clean, well-tested, and scalable Python code for model training, evaluation, and production integration.
Collaborate with backend and infrastructure teams to integrate models into real-time processing pipelines.
Tune models and pipelines for performance, inference speed, and accuracy on cloud and on-premise environments.
Maintain and improve data pipelines for training and validation, including annotation workflows and dataset versioning.
Experiment with techniques such as transfer learning, active learning, and self-supervision to reduce data dependency.
Participate in code reviews, technical discussions, and roadmap planning.
What you need Bachelor's, Master's or PhD degree in Computer Science, Engineering, or a related field.
2-3 years of industry experience applying computer vision or deep learning in production systems.
Proficiency in Python and deep learning libraries such as PyTorch (preferred) or TensorFlow.
Solid understanding of machine learning workflows and CV techniques (object detection, image classification, tracking).
Experience building and debugging ML pipelines end-to-end, from data prep to deployment.
Familiarity with version control, testing, and software engineering best practices.
Strong communication and collaboration skills.
Preferred Qualifications Experience with video processing, streaming, or encoding pipelines.
Familiarity with edge computing and low-power ML processors.
Experience building ML systems utilizing the Microsoft Azure cloud.
Exposure to MLOps tools.Contributions to open-source projects or published research in ML/CV.
Familiarity with foundational models and vision-language models.
What we offer A competitive compensation package, including base salary and stock options.
The opportunity to work in a startup environment, where your contributions directly impact the company's growth and success.
Access to cutting-edge technology, tools, and datasets to drive meaningful applied research work.
A collaborative team environment with strong mentorship and learning opportunities.
A remote-first work environment with flexibility and autonomy.
Important InformationEAIGLE is an equal-opportunity employer dedicated to building a diverse workforce.
We encourage applications from all qualified candidates and will accommodate applicants' needs throughout the recruitment, assessment, and selection process.
If selected to participate in the process, please inform the company of the nature of any accommodation you require.