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: Bachelor7s 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 quick-paced environment

📌 ML Engineer - Computer Vision (Hyderabad)
🏢 Soothsayer Analytics
📍 Hyderabad