AI Engineer

• To research modify and apply data science and data analytics prototypes.
• To create and construct methods and plans for machine learning
• Employing test findings to do statistical analysis and improve models
• To search the internet for training datasets that are readily available
• ML systems and models should be trained and retrained as necessary
• To enhance and broaden current ML frameworks and libraries
• To create machine learning applications in accordance with client or customer needs
• To investigate test and put into practice appropriate ML tools and algorithms.
• To evaluate the application cases and problemsolving potential of ML algorithms and rank them according to success likelihood
• To better comprehend data through exploration and visualization as well as to spot discrepancies in data distribution that might affect a model s effectiveness when used in practical situations

• Data Modelling
• Natural Language Processing Word2vec Sentiment Analysis Summarisation Gensim and NLTK
• Unix & Linux Servers
• Programming Languages C C Python and Java
• Spark and Hadoop

• Advanced math and statistics knowledge particularly in the areas of calculus linear algebra and Bayesian statistics
• Advanced degree in math computer science statistics or a related field
• A master s degree in artificial intelligence deep learning or a related discipline
• Strong teamwork problemsolving and analytical skills.
• Abilities in software engineering
• Knowledge of data science
• Languages for coding and programming such as Python Java C C R and JavaScript
• Practical understanding of ML frameworks
• Practical familiarity with ML libraries and packages
• Recognize software architecture data modelling and data structures
• Understanding of computer architecture

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