Machine Learning Engineer IV - Biometrics in भारत

About the Role :We are looking for a Machine Learning Engineer with strong expertise in Computer Vision and Biometrics to design, build, and scale production-grade face recognition systems. The ideal candidate should have hands-on experience developing deep learning models, optimizing them for real-time inference, and deploying end-to-end ML pipelines on cloud https://jobeax.com/link/aVGYzAkvI1UJhlBL Responsibilities :- Design and develop computer vision models for face detection, face recognition, face quality assessment, and facial attribute analysis.- Train, fine-tune, and optimize deep learning models using PyTorch, TensorFlow, and/or JAX.- Build and maintain end-to-end ML pipelines covering data ingestion, preprocessing, training, deployment, and monitoring.- Design automated data pipelines using Apache Airflow.- Curate balanced datasets and leverage synthetic data generation techniques to improve model quality and diversity.- Optimize models for production inference using ONNX, TensorRT, quantization, and model distillation.- Deploy and manage ML workloads on AWS (SageMaker, EC2, EKS).- Perform benchmarking, fairness analysis, and performance evaluation across diverse datasets.- Collaborate with engineering and product teams to build scalable, low-latency biometric solutions.- Mentor engineers and participate in architecture and design https://jobeax.com/link/oZQFhqxglZrlg0Hz Skills :- 5+ years of industry experience in Machine Learning.- Minimum 3 years of hands-on experience in Biometrics, Face Recognition, Face Verification, or Face Analysis.- Strong expertise in Computer Vision and Deep Learning.- Hands-on experience with PyTorch, TensorFlow, or JAX.- Strong programming skills in Python.- Experience with OpenCV and related computer vision libraries.- Experience building production-grade ML pipelines.- Hands-on experience with AWS (SageMaker, EC2, EKS).- Experience with Kubernetes, Docker, and cloud-native deployments.- Experience optimizing models for low-latency inference. (ref:hirist.tech)