ML Engineer - Computer Vision

Job Responsibilities

• Develop and train computer vision models for tasks such as image classification, object detection, and segmentation.
• Work with image datasets, including data cleaning, annotation support, preprocessing, and augmentation.
• Apply deep learning frameworks to build and improve model performance.
• Implement and test approaches for anomaly detection, including unsupervised defect localization using PatchCore, and work with modern architectures such as Segment Anything (SAM) and Swin Transformers.
• Apply standard machine learning techniques such as Regression, Gradient Boosting, and Time-Series methods to integrate visual data with structured metadata for business insights.
• Evaluate model performance using metrics such as mAP, precision, recall, and F1-score, and follow established validation approaches to ensure model reliability.
• Assist in integrating models into existing pipelines and support deployment efforts.
• Work closely with cross-functional teams to communicate results to technical stakeholders and clients.

Technical Skills & Stack

• Computer Vision & Deep Learning (Core Focus): Libraries: PyTorch, OpenCV, scikit-image, Detectron2, MMSegmentation, and anomalib.
• Architectures: ResNet, Faster R-CNN, Swin Transformer, Autoencoders (SAE/VAE), and Masked Autoencoders (MAE).
• Concepts: Image classification, object detection, segmentation, basic CNN architectures Machine Learning & Data Science: Techniques: Supervised/Unsupervised learning, XGBoost, LightGBM, Random Forest, PCA/SVD (Dimensionality Reduction), and Cross-Validation.
• Libraries: Scikit-learn, XGBoost, Pandas, NumPy, SciPy, and Matplotlib.
• Data & Tools: Basic SQL knowledge Familiarity with Git or version control Experience working with structured and unstructured datasets

Education & Experience Experience:

• 4-5 years of overall experience, with recent hands-on work in Computer Vision projects for at least 1 year
• Education: Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
• Must-Have Requirements
• Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow)
• Recent experience working on Computer Vision use cases
• Understanding of core computer vision concepts (CNNs, image preprocessing, model evaluation)
• Ability to write clean Python code for data processing and model development
• Strong willingness to learn and work in a fast-paced environment .