Experience: 4+ Years

About the Role:

Soothsayer is seeking a Data Scientist / Machine Learning Engineer with hands-on experience in Computer Vision to join our analytics team. You will work on developing and improving AI models for visual inspection and image-based analysis, supporting real-world industrial use cases.

This role is focused on implementation, experimentation, and continuous improvement of models under guidance from senior team members.

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 contemporary 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

📌 Computer Vision Engineer (India)
🏢 Soothsayer Analytics
📍 India