Job Description

SR. AI DEVELOPER 5 - 8+ YEARS EXPERIENCE

The position requires a solid understanding of an experience with deep learning in particular web design training evaluation and optimization of convolution neural net CNN architecture in the context of object recognition scene segmentation or classification

Mandatory experience in computer vision of machine language strong programming skills in C + + Python MATLAB and Rapid prototyping experience is required
Responsibilities
• Develop state of art computer vision algorithms for object detection classification and recognition
• Experience with at least one major deep learning Framework such as CAFFE THEANO TORCH TENSORFLOW
• Self-motivated who keeps up to date with the current state of computer vision and deep learning techniques /architecture
• A solid background in machine learning classification concept, vision image processing concept
• Minimum of 2 years’ experience in algorithm implementation in C++ and Python
• Hands on experience with computer vision or robotic systems operating on a real-world data set
• Develop computer vision techniques for object detection discrimination features parts-based modelling SVM / LSVM classifiers of CNN based detection and for facial analysis phase detection Landmark detection recognition classification and cost estimation
• Prototype hardware and software solutions for detection, classification, and recognition.

AI DEVELOPER 2 - 4 YEARS EXPERIENCE
This Position requires a mandatory experience in Computer Vision or Machine Learning
Responsibility
• Developing using Python Web Framework (Flask, Django), Python Data Science Framework (scikit-learn, SparkML API Management Framework. MEAN Stack (ELK-Elasticsearch, MongoDB) and Business Intelligence tools like Tableau (is PLUS)
• Developing in C++, Python in Linux environment. (Programing skills with multithreaded GPU CUDA computing and API solutions (is PLUS)
• Strong understanding of a linear algebra optimization probability statistics and experience machine learning methodologies such as classification clustering Matrix factorization predictive analysis decision trees support vector machines neural network deep learning
• Experience with machine learning algorithms frameworks like Caffe, TensorFlow and convolution neutral network architecture SSD, YOLO yellow forming a real time object detection and classification is a must
• Demonstrated ability to produce production quality code working in a fast-paced dynamic team
• Though knowledge of software development best practices coding standards code reviews source control management build process continuous integration and continuous delivery
• Ability to learn new technologies quickly


AI TESTER 3+ YEARS EXPERIENCE

• Experience in preparing test strategy developing a test plan details test cases writing test strips by decomposing Business requirements and developing test scenarios to support quality deliverable
• 3 years of experience in relational database with solid understanding of relational database Technologies including SQL programming
• Proven Experience in ETL testing using SQL server to validate ETL and troubleshoot data quality issues
• Experience working with large volumes of complex data preferably in distributed Framework such as Spark
• working with large data sets, Strong knowledge of data analysis, data transformation, conceptual data Modelling and meta data management.

Responsibilities
• work with the data management team to document the data landscape and identity data quality problems through data profiling including but not limited to column level cross cable and cross platform profiling to identify Caps in parent child relationship of data and or data inconsistency and business rule profiling to find a data that does not conform to established business rules
• Creating and uploading at training data set to test and confirm the algorithm is a learning/reacting correctly
• use the metaphoric testing technique to test the production of the models
• use the dual coding technique to compare the predictions of the model created using different algorithms
• create different data slices and test the predictions across these data slices.
• Do white box testing of ML models by examining some of the following
Data
Features
Aspects of ML models
ML pipeline

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Skills

Python Developer , Mathematics Teacher , APIs ,

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Qualifications