A Modern Marvel: What a Machine Learning Engineer Actually Does

These days it is not too far-fetched to say that the phrase “machine learning” is thrown around a lot in the tech world, and as a result, machine learning engineers are on everyone’s hot list. Many people know that they need machine learning engineers to get jobs done, but most are not aware of what, exactly, a machine learning engineer does on a day-to-day basis. Read on to correct this dearth of information and enhance your company’s understanding of what the machine learning engineers are actually doing.

Happy Medium: The Middle Person Between Data Science and Software

All day, data scientists strive to come up with big ideas and models that will use every huge packet of data they have. Engineers and programmers will try to perfect their programs so your company’s software is strong. For machine learning to work correctly, both of these worlds must come together. Luckily, this is exactly what a machine learning engineer is trained to do. Many machine learning engineers have the programming knowledge required to tweak models and fine-tune software, and they also possess a deep enough understanding of data science to know what an effective, scalable data framework looks like. The data scientist and the engineer don’t cross-train because they’re specialists, but a machine learning engineer is the critical bridge between the two workers, and they will make these processes run as smoothly as they can.

Reality Shapers: Bringing Lab-tested Models to Life

Many technicians and engineers will watch software programs run through tests all day to tweak things further toward perfection, and the framework will hold up all right. Sending that program and its framework into the real world, however, is a different task entirely. The inputs and feedback inherent in a real setting, where many different users will use the technology to do many different things, are enough to strain even the most finely tuned products. Yet someone has to make sure your products continue working, even when unforeseen developments affect them. A machine learning engineer has the knowledge and skills required to put your products safely into the real world, and they will do everything they can to keep software apps and products running smoothly so customers are happy.

Process Perfecters: Testing and Improving Every Aspect of Technology

Having the knowledge to keep software running smoothly involves another important job: testing and improving models and products. A machine learning engineer not only keeps your programs up-to-date, they are also the team members who are most capable of seeing how to improve your programs. This is invaluable. Machine learning engineers are trained to spot inconsistencies and flaws, and they can smooth out these kinks and push your product further than even the data scientists thought it could go. Machine learning engineers may be at the center of your data technology team, but they are truly on the cutting edge of technological prowess.

When your company needs a tech-savvy every person to make things run smoothly, a machine learning engineer is your best bet. They have enough knowledge to be a jack-of-all-trades, and their specialized skills ensure they will improve every aspect of the technology they tinker with.

Visit www.PROPRIUS.com for more information on how to improve your team and career. PROPRIUS is an Artificial Intelligence Industry recruiting firm dedicated to projecting organizations to the next level.

If you are ready to accelerate your team, then schedule a 10-minute discovery call at https://PROPRIUS.as.me/Discovery. We have a dedicated search process designed to locate, connect with, and deliver the most talented candidates.

If you are looking to propel your career, then schedule a 30-minute intake call at https://PROPRIUS.as.me/Intake. We identify the top Engineers in the Artificial Intelligence Industry that generate results, create opportunity and inspire others to perform their best work.

Joshua Crawford | Managing Director | PROPRIUS

Mastering Business Operations: How to Become a Great COO in the AI Industry

Every business has its top-level team, and the chief operating officer is one of the top-level managers at most companies. Following the path to become a COO is no small feat but joining the upper echelon of company management is certainly possible. Follow these tips, and you may find yourself with the COO title sooner than you’d think.

Get a Solid Educational Base: The Bachelor’s Degree

Going to school to study business is a great way to start on the path toward becoming a COO, and the absolute minimum education suggested would be a bachelor’s degree. The preferred areas of study are all business-related, of course, and the best choice for rounding out your business knowledge is a Bachelor of Business Administration degree. Studying these subjects should give you a solid understanding of business, management, and the realities of the working world.

Double Down on Education: The Master’s Degree

Although it is possible to become a COO without a master’s degree, the additional education and effort involved in obtaining a master’s degree go a long way toward impressing the companies you may wish to work for in the future. Once again, business administration is the most important area of expertise, so obtaining an MBA (Master of Business Administration) degree is paramount to your success. This educational realm will cover teamwork, guiding co-workers effectively, economics, and statistics, which are all the bread and butter of a COO’s responsibilities.

Look at the Big Picture: Understand Business Process Design

As the COO of a successful company, it will be your job to look at the business as a complete process from top to bottom. Knowing how to meet goals through efficient and sensible work design is a must, as is solving problems within the business structure. When you are capable of looking at your company’s resources and designing plans that utilize those resources effectively, you will be that much closer to becoming a great COO.

Give Honest Assessments: Evaluating Your Operations Strategies

Naturally, a chief operations officer is in charge of business operations. Part of operating a business is determining which processes are working and which are not and taking steps to work on streamlining the processes that work. When you determine that a process is not working as well as it should, it is your job to figure out why and assess whether it is worth working on to improve that process. Finding the processes that push the company ahead in a lucrative and progressive way is your ultimate goal as a prospective COO, so make sure you can mesh corporate goals with your operational strategies.

Keep the Peace: Foster Positive Human Resource Policies

The most important aspect of any company is its treatment of employees, and a good COO can motivate employees to meet goals while growing their knowledge and skillsets. A good COO will also lead by example by partaking in productive and effective communication; this will encourage employees to do the same, and the flow of information will improve, along with morale.

It is possible to become a COO if you follow the guidelines above, and if you master these behaviors, you may even become a great COO.

Visit www.PROPRIUS.com for more information on how to improve your team and career. PROPRIUS is an Artificial Intelligence Industry recruiting firm dedicated to projecting organizations to the next level.

If you are ready to accelerate your team, then schedule a 10-minute discovery call at https://PROPRIUS.as.me/Discovery. We have a dedicated search process designed to locate, connect with, and deliver the most talented candidates.

If you are looking to propel your career, then schedule a 30-minute intake call at https://PROPRIUS.as.me/Intake. We identify the top Engineers in the Artificial Intelligence Industry that generate results, create opportunity and inspire others to perform their best work.

Joshua Crawford | Managing Director | PROPRIUS

Build the Best Infrastructure: Finding Talented Data Engineers

Big data is approaching and it’s here to stay, so the best tech companies are looking for better and faster ways to leverage all that data to improve operations and increase profits. A good data engineer knows how to funnel all that data into a packet that is easy to use and understand. Your company can benefit from the skills a data engineer brings to the table, and we’ve got tips that will help you hire the most effective data engineers you can find.

Data Systems vs. Data Sets: Engineers Build Flexible Systems

A data scientist is the wizard who will look at all the relevant data you have on file and determine a useful conclusion from it, but first the data must be sorted and presented in such a way that it makes sense to the reader. This is where a data engineer comes into play. A good data engineer will build the framework that houses your data and find ways to logically separate data into sets within that framework, all to ease the burden placed on your data scientists. The data engineers take the nebulous data and wrangle it down to understandable parts, while the data scientists use those parts to extrapolate a larger conclusion or concept. The whole process may be likened to a sideways hourglass, with a lot of big data being winnowed to smaller portions, which are then expanded into big concepts again. This process is made possible by the data engineers.

Simplified Datasets Lead to Efficient Machine Learning

Ultimately, big data requires machine learning to streamline and expedite its digestion, and this is another area where data engineers excel. Many data engineers understand the complexities of machine learning models, so when a learning process is taking a little longer than it should to complete, a good data engineer can come along and edit the machine learning model to make it more efficient. When your company is on the lookout for competent data engineers, be sure to look for engineers who have experience with machine learning; the best data engineers can use knowledge of machine learning to maximize your company’s digestion and analysis of data.

Basic Building Blocks: Good Data Engineers Know the Fundamental Languages

Many of the critical programming and developing jobs nowadays require knowledge of several programming languages, and it is vital that the data engineers your company hires are fluent in a wide variety of these languages. Python is ubiquitous now, but many program foundations rest on lower-level languages such as Scala and C++; a really talented data engineer will know how to program in all these languages in order to bring the bigger picture into focus. The well-rounded nature of a talented data engineer translates well into other data-related jobs, so it may be helpful for your company to look for engineers who have dabbled in data science and coding.

Clearly, a good data engineer takes a holistic approach to data analysis, moving from big data to streamlined data sets and back to big conclusions. If your company can find workers who can systematize data and understand it while refining machine learning, you will have more than a good data engineer.

Visit www.PROPRIUS.com for more information on how to improve your team and career. PROPRIUS is an Artificial Intelligence Industry recruiting firm dedicated to projecting organizations to the next level.

If you are ready to accelerate your team, then schedule a 10-minute discovery call at https://PROPRIUS.as.me/Discovery. We have a dedicated search process designed to locate, connect with, and deliver the most talented candidates.

If you are looking to propel your career, then schedule a 30-minute intake call at https://PROPRIUS.as.me/Intake. We identify the top Engineers in the Artificial Intelligence Industry that generate results, create opportunity and inspire others to perform their best work.

Joshua Crawford | Managing Director | PROPRIUS

Keeping AI Industry’s Talented Engineers Happy at Work

In the world of tech, turnover rates are high and money usually does the trick of lowering them – at first. Keeping talented engineers around is difficult, but there are important steps your company can take to ensure top tech talent stays within your fold, happy and productive.

Focus on Meaningful Differentiating Factors

Money is certainly a good motivating factor, but it is not the only thing that will keep great employees around. A good company mission and/or a unique company culture can make all the difference when it comes to talent retention. In fact, roughly 50% of engineers say they would take home less money if it meant working for a brand they believe in or at a company that makes them feel at home. Meaningful missions and culture can help you retain top tech talent.

Find What Makes Your Company Shine

There’s something to be said for uniqueness. Every company should have at least one factor that sets it apart from the competition, and yours is no exception. Once you and your employees know what makes your organization special, use that as a draw when recruiting new talent. This will help attract the best fits for your company, and in the long run, the meshing of your company’s uniqueness with that of your employees will ensure long-term productivity and happiness.

Don’t Be Shy About What You Need

When seeking top tech talent, your company should look for potential hires who undoubtedly mesh well with the already-established culture of your team. While the concept of fitting in is an important one, so is expanding your company’s toolset. This means that it is important to also find potential talent with a knack for technologies you haven’t worked with, or the willingness and drive to learn new technologies. Finding a good fit that also encourages growth will be essential in retaining satisfied and productive engineers.

Give Machine Learning Engineers Independence

Welcoming members of your technology team to the table when a big decision is being made is one surefire way to keep your engineers happy. Giving engineers the space to make decisions for themselves and the team fosters creativity and responsibility while encouraging an active team mentality. When issues or mistakes are found, don’t blow up over them. Instead, use them as learning experiences and building blocks for a more competent, informed engineering team.

Be Clear About Growth Potential

There is nothing worse than feeling ready for progression but finding you’re blocked by some obstacle. Your company should tell engineers how they can move forward so they can actively pursue their goals and grow in those pursuits. Provide detailed paths toward advancement so every employee understands what they must do and where they must be in terms of skills in order to move ahead on their technological journey.

A Learning Employee is a Happy Employee

The best sort of culture for machine learning engineers is one that encourages and stimulates their minds. Provide as many opportunities for learning and growth as you can, and your engineers will stay invigorated. With seminars, meetings of the minds, and conferences, there are many ways to share new information with people, and the more information your engineers can utilize, the better and happier they will be.

Visit www.PROPRIUS.com for more information on how to improve your team and career. PROPRIUS is an Artificial Intelligence Industry recruiting firm dedicated to projecting organizations to the next level.

If you are ready to accelerate your team, then schedule a 10-minute discovery call at https://PROPRIUS.as.me/Discovery. We have a dedicated search process designed to locate, connect with, and deliver the most talented candidates.

If you are looking to propel your career, then schedule a 30-minute intake call at https://PROPRIUS.as.me/Intake. We identify the top Engineers in the Artificial Intelligence Industry that generate results, create opportunity and inspire others to perform their best work.

Joshua Crawford | Managing Director | PROPRIUS

How to Become a Better Machine Learning Engineer

As a machine learning engineer, you know the value of improvements, no matter how small they seem. Here we have a variety of suggestions for improving your performance as a machine learning engineer so you can continually improve yourself and do better work in the field of machine learning.

Love the Steady Approach: Enjoy Iterative Development

Crafting a complete machine learning model feels great, but it does not happen in one attempt, nor does it happen fast. Starting with a very basic foundation and building upon it over many updates and improvements is essential to mastering development processes, and you will be a better machine learning engineer if you learn to like these iterative processes.

Achieving the Apex: Know When to Stop Updating

While it may be good to iterate on your models, there is a point when the updates you program no longer return adequately on your investment in them. You should know when you can stop developing a program, and allow it to operate and breathe for a few moments.

Wanting to Know: Be Curious About Things

Good machine learning engineers look at the world and wonder how things work, and why certain things happen a particular way. This curiosity translates well when programming a machine learning model as good models require the curiosity to know how and why the data changes operations.

Building on Errors: Be Okay with Failure

One of the constants in science is the inevitability and importance of failure. Great lessons can be learned when processes and programs go awry, so learn to be okay with failure. When something goes wrong, look into it, and use that opportunity to push your understanding even further.

Reading Data Accurately: Have Keen Data Intuition

Good machine learning engineers can look at data and read it in ways that don’t make sense to others, and this is a good thing. Work on spotting patterns within data so you can read them and visualize them, then figure out how to model them in your programming language of choice.

Defining Experiment Parameters: Know How to Gauge Good Metrics

Every model and program needs to have a way of measuring success and failure, and this means you need to understand metrics. The ability to set sensible metrics for your machine learning models is crucial to your efficacy, and working on your metrics literacy will only improve your skills as a machine learning engineer.

Addressing Many Issues at Once: Know a Broad Bug Fix

Sometimes, you need to fix several bugs at the same time. It is good to fix single issues, too, but the ability to wrangle several issues together and blast them all away with one update will put you miles ahead of your peers.

Understanding General Users: Put Yourself in Customers’ Shoes

You might know what you want in a device or a program, but you think differently from many people. Instead, imagine the future users of your work, and create something that is pleasing and enjoyable for them.

The life of a machine learning engineer is rife with opportunities for improvement, and if you work on any or all of the areas described above, you’ll be one of the best machine learning engineers out there.

Visit www.PROPRIUS.com for more information on how to improve your team and career. PROPRIUS is an Artificial Intelligence Industry recruiting firm dedicated to projecting organizations to the next level.

If you are ready to accelerate your team, then schedule a 10-minute discovery call at https://PROPRIUS.as.me/Discovery. We have a dedicated search process designed to locate, connect with, and deliver the most talented candidates.

If you are looking to propel your career, then schedule a 30-minute intake call at https://PROPRIUS.as.me/Intake. We identify the top Engineers in the Artificial Intelligence Industry that generate results, create opportunity and inspire others to perform their best work.

Joshua Crawford | Managing Director | PROPRIUS

The Long Climb: How to Become a CEO

Not every worker involved in business wants to be a CEO, but if you’re looking to be the leader of a successful company, there are some general pieces of advice you should follow to increase your chances of making it. Let’s take a look at them.

Start Early and Study the Right Topics

While many people don’t know what they want to be when they grow up, the path to becoming a CEO is easier if you know early and start preparing as early as possible. If it is possible for you to study business and economics-related subjects before you enter college, do so. Also, participate in extracurricular activities that involve business and management; it can be useful to start your own fledgling business at this point or start a club for young entrepreneurs. The earlier you start this process, the better.

Keep Studying and Get a College Degree

With early education as a foundation, you can go to college confident in your abilities to get the job done. Studying enough to earn a degree takes willpower, fortitude, and dedication, all of which are traits you’ll need if you wish to succeed in business. Naturally, you’ll want to study subjects that are affiliated with business, so focus on business, economics, and/or accounting to give yourself the core knowledge you need.

Other subjects are helpful as well. For example, engineering is huge right now because of the monumental advances in tech sectors over the last few years. Liberal arts degrees may sound strange, but they round out your resume and give you varied experiences, which are important in the grand scheme of things; they will impress your future employers.

Graduate to the Real World and Work

You may have worked before, but after college, it’s time for you to dedicate yourself to work. If you have figured out your dream career, that’s a plus – you’ll want to enter that field as soon as possible so you can begin honing your skills and gathering more experience. If you entered your dream career before or during college, that’s even better. The longer you stay in one career field, the more likely it is that you’ll become a CEO. Make sure you work on honing your communication skills, your grasp of the big picture, your attentive listening, your network, and your leadership skills; these are the key components you’ll need to become a CEO.

Demonstrate Your Abilities and Get Promoted

By working on all the aforementioned qualities, you’re already looking like CEO material. The big push now is accepting tasks that you may not be the best at; if you volunteer for difficult jobs and learn something along the way, your experience and value to the company increase. Even if you make mistakes, you’re learning from those mistakes, and those experiences enhance your resume and therefore your chances of getting promoted. Work with people and show you can manage them effectively. A CEO is a leader of people, after all.

Once you’ve demonstrated your value to the company, sit down and show them why you deserve promotions. After you’ve done this a few times, chances are good that you’re a front-runner for the top spot of CEO.

Visit www.PROPRIUS.com for more information on how to improve your team and career. PROPRIUS is an Artificial Intelligence Industry recruiting firm dedicated to projecting organizations to the next level.

If you are ready to accelerate your team, then schedule a 10-minute discovery call at https://PROPRIUS.as.me/Discovery. We have a dedicated search process designed to locate, connect with, and deliver the most talented candidates.

If you are looking to propel your career, then schedule a 30-minute intake call at https://PROPRIUS.as.me/Intake. We identify the top Engineers in the Artificial Intelligence Industry that generate results, create opportunity and inspire others to perform their best work.

Joshua Crawford | Managing Director | PROPRIUS