Getting into Your First Artificial Intelligence Job, the Sooner the Better it is for your Career
Published on 23 July 18
Robert0
Artificial intelligence is in its infancy. Businesses are eager to hire people who can help them adapt and then move ahead.
Artificial intelligence is already reshaping society as we know it in both business and consumer realms. Early use cases with Alexa, autonomous vehicles and AI-driven supply chains provide just a glimpse of the disruption that AI is poised to deliver in the near future and for years to come.
Yet despite all the AI hype and initial successes, it remains in its infancy. That makes now the ideal time for young people to build the knowledge, skill sets and connections they need to capitalize on the fast-growing market for AI jobs and build a strong AI career.
Career Progression/Transition into Artificial Intelligence and Machine Learning?
Get Career Advice from Artificial Intelligence & Machine Learning experts!
Get Career Advice from Artificial Intelligence & Machine Learning experts!
One reason is simply practical. Gartner predicts that AI may eliminate 1.8 million jobs by 2020, yet is on track to create 2.3 million new positions. It clearly makes sense to map out an AI career path as new roles emerge that focus on problem-solving, collaboration and strategic decision-making.
AI has been called the next Industrial Revolution, and I think that analogy is spot on. The convergence of machine learning, big data and internet-scale cloud compute power is opening opportunities to transform healthcare, grow the economy, reduce waste, save energy, improve education, strengthen security and decrease poverty.
There’s virtually no area of society that will be untouched by AI. Given the myriad possibilities, how does a young person chart his or her course in the AI field?
Practical steps to an AI career.
One first step is to simply narrow down key interests and strengths. AI offers technological roles in data science, machine learning development and architecting an AI technology stack. And it offers plenty of positions as a user or analyst with AI software, or in sales and marketing, HR, customer support and more.
Company type is another important consideration, as B2B and B2C can be distinctly different work environments. Candidates should also target industries they gravitate toward, be it technology, manufacturing, retail, higher education, services or others. To narrow down interests, hands-on research and learning is available through avenues such as:
Prepare for Artificial Intelligence and Machine Learning Job Interviews with Interview Guidance on MyTechlogy for FREE!
AI and data science courses.
Many free and low-cost online learning opportunities in AI can be found at providers such as Udacity, Coursera, Codeacademy and fast.ai. These courses are a great way to build knowledge and enrich a resume.
Mastering Python (Programming language) is the key to master Machine Learning.
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Industry and company conferences.
AI experts and thought leaders discuss trends at conferences hosted by NIPS, Re-Work, O’Reilly, Gartner and others, while AI vendors also sponsor conferences. Students and young professionals are often able to gain free or discounted admission.
Career Advice From Machine Learning & Data Science Experts
There is no one size fits all solution. Your situation could be different (educational background, experience etc.), this is where experts and mentors from Machine Learning & Data Science field understand your profile better and guide you in the right path.
- Arihant Jain (Specialist: Machine Learning, Data Science, Predictive Modelling)
- Jose Munoz Mata (Specialist: Data Science, AI, Career Development)
- Ujjyaini Mitra (Specialist: Data Science, Career movement to Data science)
- Mario Lewis (Specialist: Data Science, Big Data and Analytics)
- Sabrish Surender (Specialist: Data Science, Big Data, IoT, Cloud)
- Harpreet Dua (Specialist: Data Science, Business Analytics)
- Ganapathy Govindan (Specialist: Data Science, Big Data)
- Tarun Sukhani (Specialist: Data Science)
General immersion.
Keeping up-to-date on fast-moving AI news and trends pays off. So does using AI products, sharing code on GitHub or entering a code contest on the global Kaggle community. In short, would-be AI professionals should learn as much as they can, as fast as they can.
With this knowledge, young people are better able to address two key questions that can guide AI careers:
- What’s my prospective employer’s technology stack?
- What are the employer’s leadership motivations and potential social impact?
As a Stanford graduate now working in artificial intelligence, those were critical considerations for me as I looked to move from traditional software companies into the AI space. I had decided to pursue an AI career because of the positive change that AI promises to unleash. It was a matter of finding an employer that aligned with my interests and skills.
The technology stack.
Impactful AI is not easy to build. It is complex, and the success of any AI company depends on a strong technology base. Yet some companies label themselves as AI simply to jump on the bandwagon. Discerning true AI companies from pretenders sets the stage for a gratifying first job and successful career.
Company direction.
What are the motivations of the leadership team? AI can have a major impact on driving positive change. However, since the technology is particularly powerful, it is important to keep in mind what the mission of the company is and the motivations of the leadership team.
With AI, keeping in mind potential social impact is also important. In particular, those job-seekers who value a role in bettering society with technology should diligently size up early successes and long-term benefits of any prospective employer.
AI is already transforming the job market. In fact, LinkedIn’s 2017 Emerging Jobs Report found that machine learning engineers and data scientists are the two fastest-growing new jobs in the U.S. Now is the time for young people to assess what a role in AI could mean and take proactive steps to launch a successful career.
Source: https://www.entrepreneur.com/article/315565
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