Role overview
We are seeking a Senior Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will design, develop, and deploy state-of-the-art*computer vision models* that power scalable, real-world solutions. You’ll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean, and modular code to shared repositories.
As part of our AI team, you’ll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands-on experience deploying computer vision models in production and applying MLOps best practices on cloud platforms.
Responsibilities
- Design, train, and fine-tune Computer Vision and Deep Learning models for tasks such as image classification, object detection, object tracking, and OCR.
- Preprocess and prepare*image and video datasets*, including data augmentation, labeling strategies, normalization, and feature extraction.
- Contribute to our machine learning repositories, extending CNN- and transformer-based pipelines.
- Optimize models for performance, scalability, and real-time inference across edge and cloud environments.
- Implement MLOps best practicesto train, evaluate, deploy, and monitor production-grade computer vision models, emphasizing clean, modular, and well-documented code.
- Collaborate with cross-functional teams to integrate computer vision solutions into end-to-end products and platforms.
- Stay up to date with the latest research and industry, applying new techniques to improve model accuracy and efficiency.
- 5+ years of experience in machine learning, with a strong focus on computer vision.
- Bachelor’s (Master’s preferred) in Computer Science, Machine Learning, or related field.
- Strong expertise in computer vision architectures(CNNs, Vision Transformers) and image processing frameworks such as OpenCV and PIL.
- Proficiency in Python and deep learning frameworks such as PyTorch and TensorFlow.
- Hands-on experience with*MLOps tools* (MLflow, Kubeflow, Docker, Kubernetes) for model deployment and lifecycle management.
- Strong communication skills, problem-solving mindset, and passion for continuous learning
Benefits
- Paid days off (i.e. vacation, sick days, bereavement leave)
- Health and Dental plans
- Retirement plans
- Employee and Family Assistance Program (EFAP)
- Employee referral program
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Machine Learning Deep Learning Computer Vision Mlops