Artificial Intelligence Engineer

Artificial Intelligence (AI) let machines (mostly computer systems or other machines embedded with computer programs) do things or perform tasks that require human intelligence such as:

• Recognition of speech and communicating, answering questions, giving insights, reacting to human emotions, etc.
• Search for information and convey the search results; analyse information to recommend possible decision options and also recommend the best possible course of action in a given situation.
• Recognize images, view objects and scenes, etc. and make inferences from observation.
• Switch on / switch off as well as control operations of a machine, equipment, or device.
• High tech Artificial Intelligence can assimilate knowledge from various sources like humans do, learn from experience of conversations with humans, understand human emotional reactions, and then make decisions on the basis of learning and experience.

In the near and not-so-distant future Artificial Intelligence will be able to handle complex human tasks such as writing a computer code, writing a poem or a song, compose a novel, operate a car, operate a spacecraft, carry out a medical surgery on a human/animal body, read a book and explain the underlying meaning, teach a student, and so on – the possibilities are enormous and some of the examples above are already in the making such as driver less cars.

Siri, Google Assistant, Alexa, Viv and other similar systems are driven by AI

If you are using an Apple phone you must already be using Siri. Siri is an AI driven personal assistant or intelligent agent which helps you to organize your daily tasks, remind you about your schedules, find the theatre where the movie you want to see is being screened and help you to book a ticket, find the restaurant you want to go for dinner and help you make the reservations, help you navigate from one place to another, and so on.Siri can even carry on some basic conversation.

Google Assistant on your android phone also do a lot although may not be doing all the tasks that Siri can do. However, Google has already launched Google Duplex which can carry out a lot of complex tasks such as calling a restaurant and make the reservations.

Alexa comes into various Amazon systems like Amazon Echo Dot. Alexa works as your personal assistant and work like Siri to a large extent. Alexa (called Alexa Hunches) can now guess what you might be thinking of – or what you've forgotten! Alexa keeps a record of what it hears every time. Viv is a new Apple AI system like Siri but it uses different algorithm which can perform much more complex tasks than Siri. Viv is still under development though.

IPSoft’s Amelia, IBM’s Watson, and similar other AI systems for enterprises

Amelia, a virtual agent deployed by many enterprises, is an advanced AI driven system which can observe, listen to, learn, understands, make inferences, and converse with people to solve their queries. Amelia is in the class of a cognitive agent, which is an intelligent system capable of cognition or ‘learning’. Many companies deploy Amelia as a Customer Service/ Support Agent, IT Operations Support Assistant, and similar other roles. Amelia has been developed IPSoft.

IBM’s Watson is an AI System which can perform a lot of basic and complex organizational tasks to reduce chances of human error and improve efficiency. Watson could be deployed as a Customer Service / Support Agent; it could be deployed as a conversational interface for any basic organizational tasks such as those of a secretary; Watson can analyse complex and large amont of data to discover patterns, trends, and help an organisation’s managers take decisions; Watson can recommend possible courses of actions too. Watson has applications across a range of industries – from media and advertising to healthcare and financial services.

Sounds exciting, isn’t it?

Over the years, AI research and development will keep on churning out more human like features in AI driven computer and other systems.

AI Experts at Toyota Research Institute are building crash-proof cars that can prevent accidents irrespective of the actions of the driver as well as smaller and more powerful batteries & fuel cells that will run longer using AI (Artificial Intelligence)/ ML (Machine Learning) technologies.

It you think a little ahead of time, consider a robotic assistant of a clinical psychiatrist or a device performing live surgeries without the intervention of a human surgeon. During the development phase, all of these will need the master expertise of an AI researcher and developer.

What will you do as an AI Engineer / AI Expert?

Build architecture, write algorithm, and write codes for AI systems

You will build system architecture, write algorithm, and write codes (called computer programs) to build intelligent systems which can perform various tasks that a human can do. System architecture defines how a system will work and what kind of hardware and software will be required. An algorithm is a set of rules or processes for computation (or calculation). An algorithm is like an elaborate and complex formula or step-by-step process for solving a problem or make a computer perform a specific task.

Research and develop futuristic AI Systems

You will work to research and develop Futuristic AI Systems which can perceive (e.g., understanding a scene, 3D vision, tracking, listening), predict (e.g., handling uncertainty, predicting human behavior, forecasting future situations), plan (e.g., understanding and reacting to human intent and plan actions according to that), learn (e.g., self-supervised learning, imitation learning, active learning, multi-task learning, adaptation to situations), reason (analyse data and situations using knowledge and experience, understand pros and cons of actions, etc.) and talk effectively with a human.

Build prototype, deploy, test, debug, and eliminate error to improve AI systems

You will build prototype of AI Systems that you research and develop; you will deploy the system into some applications in industries or in day-to-day life; you will test performance of the system and eliminate bugs or errors for performance improvement.

Invent and model AI solutions for problems and applications

You will invent new AI technologies, new applications of existing technologies, AI platforms and tools. You will build new applications in AI technologies such as cognitive computing, neural engineering, machine learning, deep learning, reinforcement learning, natural language processing, computer vision, and optimization.

You will build machine learning models (models represent a process as to how machines can ‘learn’ to perform a task) to solve a real life problem or for developing a real life application using complex mathematical theories such as Linear Algebra, Markov Modelling, Decision Tree Analysis, Bayesian Networks, etc.

You will write codes to develop artificial neural networks (which work like the neuron networks in human nervous systems); develop computational methods using parallel and distributing computing (using these, a very large amount data could be processed in a little time).

Key Roles and Responsibilities

• Research on AI topics and build prototype on identified areas.
• Design experiments for testing hypotheses for AI technology or solution development.
• Suggesting cutting edge solution to solve AI related problems.
• Devise data-driven models of human behavior.
• Develop Machine learning model.
• Develop deep learning architecture and algorithm; neural engineering architecture and algorithm; natural language processing algorithm; and algorithm using other AI technologies.
• Develop logic and rules for data mining.
• Write codes (computer programs) to build AI systems.
• Build and deploy prototype AI solutions to demonstrate ideas and prove concepts.
• Research, develop, and optimize AI applications.
• Perform research to advance the science and technology of intelligent machines.
• Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities).
• Apply knowledge of relevant research domains along with expert coding skills to platform and framework development projects.
• Design machine learning systems.
• Research and implement appropriate Machine Learning algorithms and tools.
• Develop machine learning applications according to Requirements.
• Select appropriate datasets and data representation methods.
• Run machine learning tests and experiments.
• Perform statistical analysis and fine-tuning using test results.

• You should have interests for Investigative Occupations. Investigative occupations involve working with ideas and quite a lot of thinking, often abstract or conceptual thinking. These involve learning about facts and figures; involve use of data analysis, assessment of situations, decision making and problem solving.
• You should have interests for Realistic Occupations. Realistic occupations involve more practical and hands-on activities than paperwork or office work. Realistic occupations often involve physical activities for getting things done using various tools and equipment.
• You should have interests for Enterprising Occupations. You should have interests for Enterprising Occupations. Enterprising occupations involve taking initiatives, initiating actions, and planning to achieve goals, often business goals. These involve gathering resources and leading people to get things done. These require decision making, risk taking and action orientation.

Knowledge

• Fundamentals of AI, Machine Learning, Deep Learning, Data Mining, Predictive Modelling, Natural Language Processing, Understanding, and Generation (NLP & NLU & NLG)
• AI capabilities - including chatbots, NLP,  Recommender Engines, Image/Video analytics, among others.
• Knowledge ofLinear Algebra, Optimization, Statistics, and Algorithms.
• Knowledge of Statistical methods; Machine Learning techniques and Algorithm such as - Neural networks, SVM, Random forests, Bagging, Gradient boosting machines (GBM), k-means++, Deep learning, Reinforcement learning, Regression, Decision Trees, Markov Decision process, etc.
• Engineering and Technology - various applications of Software Engineering; this includes knowledge about design, development, prototype testing, installation and maintenance.

Skills

• Programming skills in C, C++, Python, Java, Julia, Scala, Lua, etc.
• Data analysis using any one of R, MATLAB, etc.
• Data processing skills using SQL, PySpark, Hadoop, noSQL, etc.
• High Scale distributed RDBMS like SQL Server, RedShift, Teradata, Netezza, Greenplum, Aster Data, Vertica, etc.
• AI Frameworks and tools such as – Microsoft BOT, scikit-learn, XGBoost, Pytorch, TensorFlow, Caffe, Theano, Keras, Spacy, H2O, etc.
• Software development environment such as Agile and Scrum
• Cloud technologies and infrastructure such as - Google, AWS, MS-Azure, Cloudera, EC2
• You should have Critical Thinking skills- Skills in the analysis of complex situations, using logic and reasoning to understand the situations and take appropriate actions or make interpretations and inferences.
• You should have Reading Comprehension Skills - Skills in understanding written sentences and paragraphs in work related documents.
• You should have Judgment and Decision Making Skills - considering pros and cons of various decision alternatives; considering costs and benefits; taking appropriate and suitable decisions.
• You should have Problem Solving Skills - Skills in analysis and understanding of problems, evaluating various options to solve the problems and using the best option to solve the problems.

Abilities

• Abstract Reasoning: The ability to understand ideas which are not expressed in words or numbers; the ability to understand concepts which are not clearly expressed verbally or otherwise.
• You should have Deductive Reasoning Ability - apply general rules and common logic to specific problems to produce answers that are logical and make sense. For example, understanding the reasons behind an event or a situation using general rules and common logic.
• You should have Inductive Reasoning Ability - The ability to combine pieces of information from various sources, concepts, and theories to form general rules or conclusions. For example, analyzing various events or situations to come out with a set of rules or conclusions.
• Mathematical Reasoning: The ability to choose the right mathematical methods or formulas to solve a problem.
• Numerical Reasoning: The ability to add, subtract, multiply, divide, and perform other basic numerical calculations correctly.

Personality

• You are always or mostly organised in your day-to-day life and activities.
• You always feel secure in your surroundings and in most situations.
• You are imaginative sometimes.
• You prefer to experience new things and have new experiences sometimes.
• You act independently sometimes but do not do so in some other times.
• You are friendly and outgoing sometimes, but not always. You prefer company of people sometimes but not always.
• You are always practical or in most situations.