The AIWare.AI platform for Financial Inclusion aims to simplify banking services by making it accessible and intuitive for consumers yet efficient for bankers.
As the Machine Learning Architect, you will:
> Be part of our team of innovators, thinkers, dreamers and doers
> Build intelligence into our products to make them run smarter.
> Sprinkle your technology magic dust on engineering teams to define and build the most optimal technical solution that is compliant and satisfies the customer.
> Partner with Chief Architect and Chef Product officer to understand the problem to be solved, break down scope, set milestones and design the technical solution
> Coordinate the efforts to understand the key customer pain points, business drivers, regulations, technological challenges, and lead the solution design to eliminate these obstacles.
> Lead the implementation of the solution and work closely with Sales & GTM teams ensuring a shared vision for the future and drive the prioritization of the implementation roadmap based on customer inputs and market drivers.
What we care about
> Share our values, of Innovation & Trust.
> Ability to think strategically about business, product, and technical challenges
> Hands on experience in designing ML models and leading development of production-grade ML projects.
> Experience of Solution Designing and expertise in designing scalable and high-performance technology solutions involving machine learning and deep learning.
> Demonstrable track record of working with Product teams, prioritizing needs, and delivering results in a dynamic environment
Preferred skills / Qualifications
> 5+ years of experience in design/implementation/ experience of Machine Learning/AI/Deep Learning solutions
> 3+ years of experience with one or more Deep Learning frameworks such as Apache MXNet, TensorFlow, Caffe2, Keras,, Torch and Theano
> 12+ years of professional experience in software development in languages related to Machine Learning like Python.
> 3+ years of experience of technical architecture, design, deployment and operational level knowledge of AI platforms, standards, protocols and devices
> Experience working with GPUs to develop models
> Experience handling terabyte size datasets
> Familiarity with using data visualization tools
> Experience working with RESTful API and general service-oriented architectures.
> Worked in building models using large scale data especially images using DL techniques like CNN/RNN
> Hands on experience in working with traditional ML problems like classification / Regression / Anomaly Detection
> Experience in working with NLP Packages (Any of Core NLP/Open NLP).
> Experience using ML libraries, such as scikit-learn.
> Experience in data engineering approaches leveraging Kafka, Spark and Big Data tools.
Good to have
> Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences
Tagged as: AI, architect, deep learning, machine learning, ML
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