Data Scientist (Computer Vision)
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Aug 11, 2026. Fractal scores B on the Alion truth index.
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Job Description
Job Title: Data Scientist - AI / Computer Vision
Experience Range: 3-8 Years
Location: Bengaluru
Role Summary
We are seeking a Data Scientist with expertise in Computer Vision and AI to design, develop, fine-tune, and deploy machine learning and deep learning solutions. The role involves building scalable AI models, working with large image/video datasets, and collaborating with cross-functional teams to deliver business-focused AI applications. The ideal candidate should have strong experience in computer vision, deep learning frameworks, and MLOps practices.
Key Responsibilities
Design, develop, and optimize AI/ML solutions for computer vision applications.
Build and fine-tune deep learning models for image classification, object detection, and image segmentation.
Process, clean, annotate, and manage large-scale image and video datasets.
Develop data preprocessing and post-processing pipelines.
Train, evaluate, and validate machine learning and deep learning models.
Monitor model performance using relevant evaluation metrics and conduct error analysis.
Perform experimentation, benchmarking, and model comparison activities.
Deploy and scale AI models in production environments using cloud and MLOps practices.
Collaborate with engineering, product, and business teams to integrate AI solutions.
Follow software development best practices including version control, testing, documentation, and reproducibility.
Required Skills
Strong proficiency in Python.
Hands-on experience with Computer Vision and Deep Learning.
Expertise in PyTorch, TensorFlow, or Keras.
Experience with OpenCV and image processing techniques.
Strong knowledge of image classification, object detection, image segmentation, transfer learning, and model fine-tuning.
Experience with ML model evaluation and performance optimization.
Knowledge of Git and software development best practices.
Understanding of MLOps concepts and production deployment.
Good-to-Have Skills
Experience with Vision-Language Models (VLMs) and Multimodal AI.
Exposure to Large Language Models (LLMs) and NLP concepts.
Experience with MLflow, Kubeflow, Docker, and Kubernetes.
Cloud platform exposure (AWS, Azure, or GCP).
Experience in healthcare, medical imaging, or similar domain-specific AI applications.
Research publications or contributions to open-source AI projects.
Knowledge of Responsible AI and AI ethics.
Soft Skills
Strong analytical and problem-solving abilities.
Effective communication and presentation skills.
Cross-functional collaboration and stakeholder management.
Research-oriented mindset with attention to detail.
Ability to work in a fast-paced, dynamic environment.
Strong ownership and accountability.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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