Architect - AI/ML

Job Description

 Strong background in AI/ML algorithms Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modelling, etc.) At least 5+ years hands-on experience with: data modelling and data engineering, feature engineering, model lifecycle management supervised and unsupervised deep learning algorithms such as convolutional neural networks, recurrent neural networks, gated recurrent units  Working in data analysis, modelling, and visualization packages in TensorFlow, Keras, Pytorch, Caffe, and Theano Experience with Natural Language processing RNN and Transformer models. Extensive background in statistical analysis and modelling (distributions, hypothesis testing, probability theory, etc.) Programming modern parallel architectures (e.g., GP-GPUs using CUDA framework Strong hands-on experience with statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.) Experience in effective data exploration and visualization Ability to work in cross functional teams Excellent written and verbal communication skills in English; the ability to convey your message to team members and other stakeholdersPreferred Qualifications Experience working with relational and NoSQL/Graph databases Familiar with Big Data frameworks (Hadoop or Spark) and cloud infrastructures Ability and willingness to multi-task and learn new technologies quickly.Responsibilities Design and implement efficient, fault-tolerant Machine Learning workflows for processing high-velocity, heterogeneous data in a production environment, including optimization of ML workflows for CPU & GPU processing Suggest, collect and synthesize requirements and create effective features. Apply research methodologies to identify the Machine Learning models for the problem at hand. Provide Architectural and Tech leadership in the ML team. Manage the full lifecycle of Machine Learning microservices, including model prototyping, training & evaluation, containerization, unit testing, performance optimization, and deployment in a Kubernetes-based infrastructure. Independently design and undertake new research as well as partner in a team environment across organizations.

Keyskills :
 Strong background in AI/ML algorithms  Experience in implementing and deploying Machine Learning

About Company

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