Machine Learning Architect

GREETINGS FROM CODEMANTRA !!!

EXCELLENT OPPORTUNITY FOR DATA SCIENCE/AI AND ML ARCHITECT !!!

Skills and Qualifications

*Strong Hands-on experience in Python Programming

*** Working experience with Computer Vision models - Object Detection Model, Image Classification

* Good experience in feature extraction, feature selection techniques and transfer learning

* Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.

* Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.

* Good experience in exploratory data analysis, data visualisation, and other data pre-processing techniques.

* Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe Good knowledge in statistics, distribution of data and in supervised and unsupervised machine learning algorithms.

* Exposure to OpenCV Familiarity with GPUs + CUDA Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.

* We are looking for a candidate with 9+ years of relevant experience , who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: *Experience with big data tools: Hadoop, Spark, Kafka, etc.
*Experience with AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
*Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.

Responsibilities
*Selecting features, building and optimizing classifiers using machine learning techniques
*Data mining using state-of-the-art methods
*Enhancing data collection procedures to include information that is relevant for building analytic systems
*Processing, cleansing, and verifying the integrity of data used for analysis
*Creating automated anomaly detection systems and constant tracking of its performance
*Assemble large, complex data sets that meet functional / non-functional business requirements.
*Secure and manage when needed GPU cluster resources for events
*Write comprehensive internal feedback reports and find opportunities for improvements
*Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model

Regards