Job Description:

A) Overall:

- Experienced Solution Architect in the Data Engineering and Data Analysis space with focus on building AI Solutions.

- Experience in devising/enhancing machine learned (DL, NN) algorithms and data mining techniques for solving complex Big Data and enabling key business use cases through completion 

-  Must have delivered valuable Insights. Candidate should have lead the AI-based engagement through completion - including collaborating with the client on value messaging, use case elaborations and managing AI Engagement lifecycle (through deployment) while managing a team.

- Excellent client facing skills - communication, facilitation and collaboration.

- Proven Solution Architecture (data / integration-based solutions) capabilities - POC / MVP to productionizing solutions.

- Should help in expanding and securing new business

- Team leadership

- Ability to Travel - international also.

- Overall experience of 15 years - specific AI experience of minimum of two years.

B) Cloud AI Platforms:

- Experience in AI Solution Stack Solutions of atleast one of the Cloud Providers (Azure, AWS, Google).

- Hands-on usage of leading tools for productionizing AI solutions 

- AWS Sagemaker and Libraries

- Azure ML components (Studio etc.)

C) AI / DL Frameworks (Atleast 2) :

- Knowledge of popular AI / DL frameworks - Tensorflow, Keras, MxNet, Caffe. CNTK, Theano / Pytorch

- Working knowledge of atleast two frameworks.

- Deep understanding of frameworks, its strength and applicable AI use-cases.

D) Machine Learning (Must have):

- Experience implementing ML algorithms such as Logistic Regression, Naive Bayes, Bayesian Network, Decision Tree, Neural Network, SVM, Boosting, K-Means, Ensembler Classifiers, Random Forest, convex optimization, transfer learning.

- Experience in frameworks such as Spark, Lucene or EMR to implement real-time ML systems

- Strong mathematical understanding.

- Up-to-date knowledge and understanding of recent trends in machine learning.

D) Should have deep expertise in atleast one of the following - Computer Vision, Speech Recognition and/or NLP.

D1 - Computer Vision:

- Experience with object detection, tracking, classification, recognition, scene understanding, facial expression analysis

- Sound background in one or more of Computer Vision like Scene Understanding, Recognition (Face, Iris, Finger, Gesture,)

- Image Processing - hands-on expertise

- Programming in C / C++ Usage of Mat lab, Open CV toolkits.

- Experience on embedded / mobile platforms and real-time implementation of complex algorithms

D2 - Speech Recognition :

- Should have good experience in speech technologies, ASR/TTS(Text to Speech).

- Exposure to speech technology tools like, HTK, Kaldi, Festival

- Prior experience in speech technologies (ASR or TTS) is required.

- Strong understanding of Machine Learning techniques especially deep learning

- Good Programming skills in C, Python & Shell scripting is desirable.

D3 - Natural Language Processing / Understanding / Generation :

- Experience with some of the NLP problems, like intent detection, sentiment analysis, NER etc

- Strong understanding of Machine Learning techniques especially deep learning

- Good Programming skills in C, Python & Shell scripting is desirable.

E) Cloud - Data Engineering (Must have):

- Proven experience working with large scale data foundations on Cloud - data acquisition, processing/transformation, feature engineering and building production quality data foundation.

- Understanding of larger Cloud Data Landscape ecosystem on Data Acquisition, Data Processing, Storage and Consumption.

- Strong experience with one of the Cloud-native (AWS, Azure, GCP) data platforms.

- Hands-on expertise in scripting - Python, R.

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