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Smoothstack reviews

Careers in Artificial Intelligence and Machine Learning

Smoothstack Reviews AI

While once reserved for our imagination, artificial intelligence (AI) and machine learning (ML) are here to stay. AI is in the top 10 trends[1] driving growth in Information Technology.   Artificial intelligence is “broadly defined as the capability of a machine to imitate intelligent human behavior,” whereas machine learning “ gives computers the ability to learn without explicitly being programmed.”[2] While AI gets most of the attention, ML is the part of AI that makes things smarter over time.  By using past data, ML allows decisions to be made by the AI.

If you are worried about the robots taking your jobs, AI is expected to create 58 million jobs[3].  Even with the pandemic, AI job growth has increased 32% since 2019[4].  AI and machine learning are being integrated into more aspects of daily life every day.

If you use Gmail or Outlook, you’ve likely noticed the text suggestions that pop up as you reply to someone. You can thank AI for that. The last time you took a flight, your pilots likely only had complete control of the airplane for take-off and landing, AI was at the helm for most of the flight.

Do you use Waze or Google Maps to estimate how much time you’ll need to drive to work? You can thank ML for that. Have you used your bank’s app to deposit a check via photo? You can thank ML for that, too.

Someone Has to Program AI

Behind all Artificial Intelligence, there’s an army of people working to make sure that the algorithms work correctly and that users find the new tools helpful rather than annoying or invasive.

AI jobs range from engineers; who build the platforms, data scientists; who monitor the trends and keep the algorithms up to date, to mathematicians; who write the algorithms.

There’s also a business side to AI and ML. Business Intelligence Developers are responsible for integrating AI and ML with a human team and keeping the business as efficient and profitable as possible. Marketing is also increasingly being driven by AI.

User experience (UX) designers work to ensure that the AI and ML being offered are things that the public can use and want to use.

In short, the range of career paths in AI or ML is rapidly expanding with no end in sight.

What’s Next for AI

Two new AI technologies were introduced in the last year, OpenAI’s GPT-3 and Google’s Deepmind AlphaFold2[5].   GPT-3 expanded language processing to allow reading, writing, and conversation with humans beyond simply programmed responses.  If you dreamed about having a meaningful conversation with a robot, GPT-3 would make it possible. 

AlphaFold2 is likely to be the future of medicine.  Its ability to break down protein structures will dramatically accelerate DNA research.  Look for new drugs and cures for rare diseases because the time and cost to do the research will drop significantly.

Many of these technologies may not be apparent to the public, but they are changing our lives.  In the coming years, we are likely to see more sophisticated physical robots showing up in warehouses and other industrial settings.  If you want a glimpse of what is possible, check out the robots of Boston Dynamics[6].

If you’d like to know more about a career in Artificial Intelligence and Machine Learning, contact us at https://www.smoothstack.com.

[1] http://reports.weforum.org/future-of-jobs-2018/information-communication-technologies/

[2] https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained

[3] https://www.bestcolleges.com/blog/future-proof-industries-artificial-intelligence/

[4] https://www.cnbc.com/2021/06/01/10-of-the-most-in-demand-ai-jobs-that-pay-at-least-95000.html

[5] https://www.kdnuggets.com/2021/01/top-5-artificial-intelligence-trends-2021.html

[6] https://www.bostondynamics.com/

Turning Data into Gold

Whether it’s visualizing and managing global supply chains or being able to track the spread of viruses, data science and analytics are changing our world.  As tech careers go, it doesn’t get much better than being a data scientist.  For the past four years, data scientist was voted the number one job by Glassdoor with an average salary of almost $140,000[1].  Companies are willing to pay a premium for this skill because data can save them billions.  In the information age, analytics is the alchemy that turns data into gold.

Career Paths

There are a variety of career paths you can take in data science, and there are plenty of jobs to be had.  The bureau of labor statistics ranks it as one of the fastest-growing career areas.  Between 2016 and 2026, data science careers are expected to grow 33.8% [2].

Data scientists take troves of raw data, organize it, and translate it so that companies can understand it and leverage it for maximum efficiency and profit. Data scientists are often the first to identify trends. They’re the forward thinkers on the team.  They regularly use a variety of programs/languages including R, SAS, Python, SQL and more.

Data analysts, on the other hand, are like historians. They use existing data to run A/B tests, which give companies objective information on which product or process is better, more efficient, or more profitable. Data analysts are the curators on the team and keep the data organized and stored.  This is a less technical position, but people in this career should still have a background in the tools the data scientists are using.

Our Robot Helpers

Artificial Intelligence (AI) and machine learning (ML) are deeply integrated with data science and analytics. As technology continues to evolve and expand into new areas of our human experience, companies are creating roles like Enterprise Architect to support business strategy alignment with technology, Applications Architect for support with UX and reach. Infrastructure Architect, to make sure that business systems are up to date and running smoothly.

Seemingly unrelated to technology, librarians are increasingly training as data scientists. Charged with cataloging and preserving the entire canon of humanity’s collective knowledge, libraries are moving their collections online and using databases to keep them safe and well-organized.

Our Medical Future

Data is also playing an increasingly important role in medicine. As we continue to map the human genome, treatments can become more and more personalized. Genetic counselors use gene-editing tools like Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to identify the most customized treatment plans. Disease mappers use data to map and track contagious diseases, like COVID-19, and use models to help doctors and healthcare workers stay one step ahead of outbreaks.  Data science has also been critical in comparing data from multiple surveillance systems and combining data sets. [3]

What’s Next

One of the things Covid has taught the data science world is that trends can be interrupted.  Models need to be revised and new variables need to be considered.  Somebody has got to sift through that data and make sense of it. There’s no reason that it might not be you.

For more information on starting a career in data science and analytics, let Smoothstack be your guide. http://smoothstack.com/

[1] https://www.northeastern.edu/graduate/blog/data-science-careers-shaping-our-future/

[2] https://www.discoverdatascience.org/career-information/

[3] https://www.cdc.gov/coronavirus/2019-ncov/php/surveillance-data-analytics.html

Smoothstack IT Apprenticeship

We live in a time when too many people interested in technology are being turned away because they don’t have the requisite experience. This doesn’t even include the two-thirds of all women who don’t even consider tech because they believe, or have been told, that the barrier to entry is too high. Smoothstack is working to change that. Smoothstack reviews their modern-day apprenticeship model, optimizing it for the twenty-first century. Smoothstack’s apprenticeship consists of 6 phases: Application Process, Engagement Period, Training, Marketing, Deployment, and Mentorship…and it all starts with you!

Application Process

First, you apply for a role that suits you best at smoothtack.com.  This action will kicks off the application process, which consists of several steps:  

1) Depending on the role, you will take a coding challenge or applicable assessment. 

2) If you pass, you will be invited to an initial pre-screen call where our recruiters will learn about your background and determine whether you would be a good fit for Smoothstack.

3) Assuming the role would be a good fit for you, you will be invited to a video screening with a member of Smoothstack’s technical team. There you will be asked technical questions to ensure you have the baseline technology requirements in order to be successful as a Smoothstackemployee. 

4) Those who excel, will receive a letter about the acceptance to the engagement portion of the apprenticeship.

Engagement Period 

Well, at this point you’ve already passed a technical screening, and we already believe that you’re a good technical fit. We still want to make sure that you also have other necessary qualities to be a SmoothstackApprentice. For example, how quickly you grasp new technical concepts, how you collaborate or communicate with your teammates, and how well you deliver requirements and meet deadlines. Those who excel in these areas will receive an offer letter from Smoothstack. Once you accept it, you’re a full-time Smoothstack employee which means the official training starts and you’re getting paid for being trained.

Employee Training 

Employee training usually takes around 12-14 weeks and is mainly project-based. As you attend daily classes with Smoothstack trainers and learn new skills, you apply them to capstone project(s) and build on top of it until your training is finished. You will work in a simulated work environment that follows Agile methodologies and will receive requirements from your product owner and Scrum master. This will prepare you to hit the ground running when you start working on Smoothstack client project(s). 


By the end of the training, you will have completed your first project. You will meet with one or more of our employer partners and present the work you’ve done during training. A client that finds you and your skills a good fit for their team will request you for their project(s). 


The 1st thing that happens is a salary adjustment. Your salary goes up from a training rate to a deployment rate. You meet your new teammates and start working on projects. Since you’re still a Smoothstack employee, we want to make sure that you are successful while working with our clients, and we are here to support you. 


Smoothstack staff will be communicating with you regularly. We want to get your feedback on your role and provide support or additional training if you need it. We will also be reaching out to your supervisors and getting feedback on your performance, and letting you know where you stand. This continues throughout the whole Apprenticeship which lasts about two (2)  years. Smoothstack believes that there are so many talented people out there that deserve to be in the Tech Industry, and we make sure those individuals claim their spot. 

Learn more about Smoothstack’s open roles by visiting:

Smoothstack Reviews Biggest IT Trends of 2021

The information technology (IT) industry is a $5B industry that plays a critical role in almost all sectors, including healthcare, manufacturing, transportation, education, and energy. As the US continues to lead in technology innovation, information technology is quickly becoming the backbone of both national security and economic growth.

Smoothstack has successfully kickstarted hundreds of IT careers for individuals across the US through their modern-day IT apprenticeship program. Their success is attributable in large part to Smoothstack’s high-quality employee training, rigorous hiring process, and adaptability to ever-changing industry needs. The IT landscape changes quickly, and paramount to providing quality upskilling is not only the ability to adapt quickly, but to also identify areas in which upcoming trends will shape IT. Here, Smoothstack reviews the latest IT trends of 2021 and how they will impact the technology industry.

Focus on Privacy 

Over the past two years, the IT sector has experienced a never-seen-before emphasis on global data protection. In 2020, the number of remote workers tripled due to COVID-19 and the need to connect the workforce within a virtual environment. As a result, companies are seeking better solutions to ensure company data remains secure within this new framework. The IT community has responded with both novel privacy-enhancing computation and cybersecurity mesh. Privacy-enhancing computation helps secure sensitive data, protecting it during processing. Essentially, this allows for collaboration without the sharing of sensitive data. Cybersecurity mesh allows business to decouple policy decision-making from policy enforcement and effectively establishes security perimeters around individual parameters rather than securing the organization as a whole. This creates a modular security architecture that is more manageable and more responsive to outside threats.

Intelligent Composable Business

One of the most talked-about trends of 2021 is intelligent composable business. This new concept leverages business capabilities and applications into interchangeable building blocks. Composable business is based on four main principles: speed through discovery, agility through modularity, leadership through orchestration, and resilience through autonomy. Intelligent composable business will not only accelerate digital business progress but will help businesses adapt to economic changes more quickly.


Although MLOps or “Machine Learning Operations” is not a recent technological innovation, COVID-19 has put a new focus on MLOps and their application. No one can deny the massive impact COVID-19 has had on the global workforce; with new changes to operational workflow, traffic patterns, and inventory management, many AI operations began to react unexpectedly and Drift. Drifting takes place when AI receives data that it was not taught to react to. One of the main functions of MLOps is to detect anomalies in ML model development and alert IT teams so they may fix the issue and make improvements.