Fynd - Machine Learning Engineer - Tensorflow/PyTorch (6-10 yrs)

Job Description :

As a Machine Learning Engineer, the purpose of this role is to work with our machine learning research team to develop, implement and deploy machine learning and deep learning models. Our core area of work is in the field of computer vision so you will require some familiarity with convolutional neural networks.

- Work on the deployment of machine learning and deep learning models.

- Help in accelerating model inference using various compression tools like onnx, Torch script, TensorRT, OpenVINO ....etc. Develop and maintain a data streaming pipeline (both batch and real-time) for data integration and large-scale machine learning.

- Deliver best practices recommendations and technical presentations around machine learning deployment including real-time modeling.

- Maintain and further enhance the internal model feature store and optimize the feature engineering script.

- Full life cycle implementation from requirements analysis, platform selection, technical architecture design, application design and development, testing, and deployment.

- Responsible for the end-to-end deployment of predictive models including scoping, testing, implementation, maintenance, tracking, and optimization of predictive models.

- Responsible for complete and accurate documentation of all development around machine learning engineering.

Some specific requirements :

- 2+ years of experience implementing and deploying machine learning and deep learning frameworks through distributions cluster and application programming in cloud platforms including AWS and GCP.

- Basic Knowledge of tools/libraries such as TensorFlow, PyTorch, Keras, NumPy, pandas etc.

- Strong understanding of data structures and algorithms and experience in Python.

- Some experience with computer vision(classification, segmentation, object detection) pipelines

- Deep experience across systems integration, information management, data management and architecture, and business analytics.

- Language: Python, Java, Scala, Unix bash script, REST API process.