Senior Data Science Engineer Computer Vision @ Uplers

Looking for a skilled Senior Data Science Engineer with 6-12 years of experience to lead the development of advanced computer vision models and systems.

The ideal candidate will have hands-on experience with state-of-the-art architectures and a deep understanding of the complete ML lifecycle. This position is based in Bengaluru.

• Lead the development and implementation of computer vision models for tasks such as object detection, tracking, image retrieval, and scene understanding.
• Design and execute end-to-end pipelines for data preparation, model training, evaluation, and deployment.
• Perform fine-tuning and transfer learning on large-scale vision-language models to meet application-specific needs.
• Optimize deep learning models for edge inference (NVIDIA Jetson, TensorRT, OpenVINO) and real-time performance.
• Develop scalable and maintainable ML pipelines using tools such as MLflow, DVC, and Kubeflow.
• Automate experimentation and deployment processes using CI/CD workflows.
• Collaborate cross-functionally with MLOps, backend, and product teams to align technical efforts with business needs.
• Monitor, debug, and enhance model performance in production environments.
• Stay up-to-date with the latest trends in CV/AI research and rapidly prototype new ideas for real-world use.

• 6-7+ years of hands-on experience in data science and machine learning, with at least 4 years focused on computer vision.
• Strong experience with deep learning frameworks: PyTorch (preferred), TensorFlow, Hugging Face Transformers.
• In-depth understanding and practical experience with Class-incremental learning and lifelong learning systems.
• Proficient in Python, including data processing libraries like NumPy, Pandas, and OpenCV.
• Strong command of version control and reproducibility tools (e.g., MLflow, DVC, Weights & Biases).
• Experience with training and optimizing models for GPU inference and edge deployment (Jetson, Coral, etc.).
• Familiarity with ONNX, TensorRT, and model quantization/conversion techniques.
• Demonstrated ability to analyze and work with large-scale visual datasets in real-time or near-real-time systems.
• Experience working in fast-paced startup environments with ownership of production AI systems.
• Exposure to cloud platforms such as AWS (SageMaker, Lambda), GCP, or Azure for ML workflows.
• Experience with video analytics, real-time inference, and event-based vision systems.
• Familiarity with monitoring tools for ML systems (e.g., Prometheus, Grafana, Sentry).
• Prior work in domains such as retail analytics, healthcare, or surveillance/IoT-based CV applications.
• Contributions to open-source computer vision libraries or publications in top AI/ML conferences (e.g., CVPR, NeurIPS, ICCV).
• Comfortable mentoring junior engineers and collaborating with cross-functional stakeholders.