Machine learning engineers are the need of the AI industry with the incredible growth of model development for various industries in the new age. Therefore, hiring a remote machine learning engineer seems to be a growing trend in the areas of machine learning, as many companies work on unique or dedicated projects for specific needs for a limited time.

Owing to the worldwide pandemic and flexible work responsibilities and duties, such experts prefer to work remotely, ensuring optimum performance. Furthermore, at Global Leadership Summit in London, 34% said that more than half of their full-time staff would be working remotely by 2020.

Tech companies also prefer to hire remote ML engineers and developers, especially AI experts, who are looking to work remotely or within a more flexible arrangement. This trend means that smart & innovative companies may be considering this pool of labors in addition to hiring onsite staff.

Working with such highly skilled professionals is not only interesting but also challenging for other professionals like data scientists, training data experts, and AI model developers. As working remotely is quite different from the onsite work process, AI companies need to know certain points before hiring a remote machine learning engineer to make sure they fill in with the apt candidature.

Also Read: How To Hire A Good Data Scientist: Five Easy Steps

Identifying the Problems Statement and Data

Before hiring a machine learning expert, a company needs to check the data they have and how much machine learning training data they require for the new employee to create a machine learning model that would work properly giving acceptable results.

Identifying the Problems Statement

Having a good data infrastructure and making sure you have data for this person to work-with is important, and it would be one of the milestones you need to reach before you start thinking about hiring someone for developing the AI model.

While on the other hand, big companies may have a plethora of data, but smaller or medium sized companies still need a huge amount and types of datasets. Hiring someone before you start collecting data might be advantageous because this person will help you in the collection process and create a major impact in the industry.

Also Read: How Much Training Data is Required for Machine Learning Algorithms

Hence, while hiring the engineer it’s important for at least one leader from the company’s engineering side and one stakeholder from the less-technical business side to meet and determine technical needs, business goals, and other qualifications required for the machine learning role.

Attracting The Right Talent to Move in the Right Direction

Appointing the candidate with the right talent is important to make sure your AI model progresses and completes with stellar outcomes. As per the research from Atlas, a remote work life maybe its advantage within the technological field. When these programmers were asked to mark a list of their preferred job benefits, vacation or days off was preferred by over 57%, while remote work was the next highest preferred benefit at 53%.

Businesses may want to start looking for freelance talent when remote work is applicable. According to the study, most software developers and machine learning engineers seem to prefer the flexibility to work remotely, and so offering it to them might give businesses in need of their talent an advantage, to acquire interesting results.

Building a Bridge for Hiring the Right Candidate

As a company begins to hire for AI or machine learning efforts, its goal should be first to find someone who is a strong, articulate communicator who understands both the technology and business requirements. Such people have the abilities of an AI engineer, but would also be able to lead or build a technical team and can communicate with non-technical people. They need to educate people, and they need to communicate what they can do and are not able to do.

While finding the bridge person, the engineering and business stakeholders who created the job listing should be involved in the interview and selection process. An already-hired AI engineer or a software engineer with strong mathematical or statistical knowledge will know what technical questions to ask, whereas a business-oriented person will be able to speak with the candidate about the company’s goals and vision.

Also Read: What is the Importance of Image Annotation in AI And Machine Learning

A talented ML engineer can communicate and articulate what they’ve done and what they will do, even when speaking to non-technical stakeholders. While business leaders may want their bridge person to have expertise in the machine learning field and academia, they may also occasionally find other individuals that are suitable as machine learning team members.

Hire the Individual Experts Rather Than Multitalented

If you are thinking about hiring one person who’s an expert in two or more AI technologies, to utilize his skills in different areas, ponder again. Hiring multiple people, each with expertise in at least one strategy, can provide some benefits. Whereas, on the other hand, if you’re just hiring one or two individuals, you’re probably looking for multiple technical trades or a ‘Master of Something’.

IT competency in ai

However, if you wish to find someone who is exceptionally good at being able to communicate and to dive deep into whatever problems you have; this person is going to do it all, if you are hiring a team, which will leave you with more options.

To understand the benefit of considering dynamic duos, let’s take an example; instead of hiring a machine learning engineer with expertise in natural language process and computer vision, an employer could choose to hire one computer vision expert with some NLP experience, as well as one NLP expert with some computer vision experience.

Hiring such individuals and putting them together will display what exactly these people are curious about. They are going to start talking to learn from one another and become thoroughly proficient over their weaknesses in just a few months’ time. With this optimistic approach, they’re going to have great ideas that they’re going to share.

Connect and Communicate Onboard Wirelessly

Hiring the remote machine learning engineers or such highly skilled professionals, needs to bring encouragement and put them through a proper channel, especially if they are working remotely.

It is important to interact with both of them as these positions can come with a lack of visibility, so you need to formally introduce people. They need to be shown where they can ask for help from each other or on what topic they need to discuss with each other.

Such employees should not just be “dropped” into a project. An employer should make sure that they have access to the data and contacts that they will require. When they match a remote machine learning expert with a company, they make sure they contact the client’s company hiring them and have full access to the data the remote worker may need. They also make sure that the contacts at the client’s company is available to onboard meetings and discussions between them properly.

Cogito Cogito provides machine learning hiring service for AI companies looking for remote machine learning engineers for model development as per their customized needs. With Cogito you can hire machine learning programmers, machine learning experts, python machine learning engineer, machine learning freelancer, or developers for azure machine learning feature engineering.

Also Read: Top Four Myths About Outsource Data Annotation Services

Moreover, Cogito is also involved in data annotation services with expertise in image annotation services to deliver high-quality training data sets for computer vision-based AI model developments. Working with a team of annotators, Cogito is an industry leader in annotation services with a scalable workforce and flexible working hours to deliver the projects before the deadlines.

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