KS
Kavi Software Technologies Private Limited
Senior Data Scientist – Computer Vision
thoraipakkam, INNa miejscuStałaPełny etat
Opublikowano 24 paź 2026
To stanowisko jest opublikowane w języku EN
Role : Senior Data Scientist – Computer Vision
Timings : 01:00 pm - 10:00 pm
Experince : 7 Years
Location : Thoraipakkam
Required Skills & Qualifications
- 7+ years of professional experience in Machine Learning with a specialization in Computer Vision.
- Advanced degree (Master's or Ph.D. preferred) in Computer Science, Electrical Engineering, or a related quantitative field.
- Expert proficiency in Python and frameworks like PyTorch, TensorFlow, or Keras.
- Hands-on experience with CV libraries such as OpenCV, YOLO, Detectron2, and MMDetection.
- Strong background in CNNs, Vision Transformers (ViT), and image preprocessing techniques.
- Proven experience deploying models via Docker, Kubernetes, FastAPI, ONNX, and TensorRT.
- Skilled in cloud AI/ML services across AWS, GCP, or Azure (e.g., SageMaker, Vertex AI).
- Deep knowledge of data structures, algorithms, and software engineering best practices.
- Experience managing large datasets with SQL, Spark, Pandas, or Dask.
- History of taking ML models from research/prototypes into scalable production environments.
- Excellent communication, problem-solving, and cross-functional collaboration skills.
- Familiarity with MLOps, CI/CD pipelines, and edge AI hardware (NVIDIA Jetson, mobile inference).
Przegląd stanowiska
Typ stanowiska
Pełny etat
Wymagane umiejętności
Machine LearningComputer VisionPython ProgrammingDeep Learning Frameworks (PyTorch, TensorFlow, Keras)Computer Vision Libraries (OpenCV, YOLO, Detectron2, MMDetection)CNN and Vision Transformer ArchitecturesImage PreprocessingModel Deployment with Docker, Kubernetes, and FastAPIModel Interoperability and Inference Optimization (ONNX, TensorRT)Cloud AI/ML Services (AWS, GCP, Azure)Data Structures, Algorithms, and Software Engineering Best PracticesLarge-Scale Data Management with SQL, Spark, Pandas, or DaskProductionizing and Scaling Machine Learning ModelsMLOps and CI/CD PipelinesEdge AI and Mobile Inference
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