The 15 best sites to hire MLOps Developers in 2024

MLOps is an abbreviation for machine learning operations. Machine learning is a type of artificial intelligence that uses data models and machine processes to teach computers how to learn things. It is a much more efficient and cost-effective way to develop artificial intelligence and gives companies a competitive edge. In this guide, discover how to hire MLOps developers to apply machine learning models to your workflow.

AI and machine learning continue to expand and be a part of all types of workflows and business models. According to Fortune Business Insights, the value of the machine learning market in 2029 will be $209.91 billion, a growth rate of more than 38% since 2022.

Having MLOps engineers on your team and using them to perfect machine learning applications benefits businesses in marketing and sales, healthcare, banking, manufacturing, retail and more. Engineers with this skillset can help companies expand their practices, improve the customer experience, anticipate customer demand, optimize the production process, detect fraud and identify future pandemics.

One instance of a successful integration of machine learning processes in an industry is retail chatbots. Companies employing chatbots saved up to 30% on customer support costs. MLOps engineers offer retail businesses a way to answer critical questions from customers instantly and resolve minor issues right away with chatbots, improving their customer service experience.

This guide walks you through the first step of implementing machine learning strategies in your business operations to be more impactful. Our goal is to show your team how to source potential new hires and freelance developers with this in-demand skill and recruit talented people.

Hiring a Freelance MLOps Developer

One of the first decisions to make before you hire a freelance MLOps developer is figuring out what type of employee you need. Depending on your needs and the size of your team, you may consider adding full-time employees, part-time workers or independent contractors to your business. Hiring permanent employees means you will likely need to invest in benefits and employer taxes via your payroll servicing system.

If you decide to work with freelance MLOps developers, you may benefit more. First, you will not have to pay extra employer taxes on a freelance contractor’s paycheck. Additionally, a remote employee who is freelance does not need a dedicated office space or company equipment. Freelancers have much more flexibility and can work on demand instead of a set schedule.

What Does a Machine Learning Operations Engineer Do?

Machine Learning Operations Engineers (MLOps) are computer programmers specializing in the ML area of artificial intelligence. They are responsible for making and using computer models to teach AI. They work with data models in production and train algorithms for large-scale models. Machine learning developers oversee the process of using data to implement artificial intelligence systems.

Why hire MLOps developers? Hiring these developers gives you a competitive edge in your field. Having someone with this expertise on your team allows you to automate repetitive tasks and work more efficiently. Machine learning engineers also offer you greater insight into your company’s metrics and data. You will be able to more effectively analyze the data your company collects and make better decisions for your future direction.

To stay competitive in the next digital age, your team needs to harness the power of AI and machine learning. MLOps devs are one of the top tech roles that could revolutionize your business objectives and open your company up to more opportunities. With MLOps developers for hire, you can streamline processes through artificial intelligence and free up your manpower for more innovation and ideas.

One example of harnessing the power of machine learning with an MLOps developer comes from ride-sharing behemoth, Uber. In a case study using machine learning strategies, Uber worked with Machine learning operations developers to create a prediction model to forecast demand for airport rides.

Uber’s challenge was balancing driver supply and demand and managing their customer’s experience. According to the developers,

Companies that hire dedicated MLOps developers can achieve more with their data and perfect their processes. The technology continues to evolve and expand as developers work more to tweak usage and specifications.

How To Hire MLOps Engineers

Being a top performer in your industry today means you need to master using data. This is where an MLOps developer comes into play. To hire the right MLOps engineer, you need a comprehensive strategy that employs different types of resources and hiring tactics.

First, your team needs to define your needs for machine learning operations. Work with your company’s data scientists, leaders and software team to determine what you require from an MLOps dev. Consider the goals you want to achieve in machine learning and artificial intelligence. Identify if you need full-time, part-time or contract work and the level of skill you want from a developer.

Next, you will need to source candidates from various places, such as freelance sites, developer firms, consulting agencies and networking events. Your team must assess different applicants and their technical skills in machine learning. Entry-level candidates may not have extensive experience in software development lifecycle, but they should have the most up-to-date knowledge about the latest trends in AI.

When looking at mid- or senior-level MLOps developers, you may see more evidence of completed projects that made an impact on a business’s bottom line. They typically have more experience in production software engineering and the management of machine learning.

Choosing a senior or mid-level MLOps engineer may give you more resources at hand, but it could also be more costly. Entry-level contractors can save you initially, but they may not have the right combination of skills and experience. Teams and management should weigh the pros and cons of each applicant before committing to their services.

What Skills To Look For When Hiring an MLOps Developer

Before choosing someone to add to your organization, you need to assess their technical skills and character traits. Look for specific MLOps developer skills that will ensure your team benefits from machine learning tasks. The average MLOps engineer should have several core competencies in technical programming, cloud expertise and machine learning practices.

Besides technical knowledge, MLOps engineers also have to possess integral soft skills. They typically work together with a team of professionals in AI, data science and software development. These are the most sought-after soft skills your team needs to recruit for in an MLOps developer:

• Ability to explain complex concepts in simple terms: Machine learning operations are a complicated concept for the average person to understand. Developers should be able to break down the ideas in simple terms for the rest of the team.

• Excellent critical thinking skills: Critical thinking ability is a must in this role. Machine learning problems are often unique and need on-the-spot solutions as they arise.

• Ease of working well with others: The person in this job must work with a variety of people on the team. They must have strong interpersonal and collaboration skills.

MLOps developers should also demonstrate several important technical skills. They should have academic credentials in computer science, programming, coding, engineering or mathematics. They should also hold certifications in technical capacities related to their role. Here is a list of preferred technical skills to seek in an MLOps developer:

• Understanding of machine learning algorithms and frameworks such as TensorFlow and PyTorch

• Coding knowledge of Python and Java

• Ability to deploy code on AWS, GCP or Azure

• Understanding of CI/CD pipelines and IaC tools like Terraform or CloudFormation

• Expertise with Docker and Kubernetes

How Much Does It Cost To Hire MLOps Developers?

According to ZipRecruiter, the average yearly salary for an MLOps developer is $87,220. This would be for a full-time engineer and does not include other incentives your company would pay for, such as benefits, health insurance, bonuses and company stock. The average hourly rate for someone in this job adds up to $51, which is a bargain if you want to work with an hourly freelancer for your project.

Tips for Writing an MLOps Developer Job Description

Since MLOps developers are in demand by companies across industries, you have to do whatever you can to attract the top candidates to work for you. Your team will need to master the art of writing a strong MLOps developer job description. Start with a captivating title, include detailed duties and responsibilities, give information about your company’s perks and have specifics about how to apply for the job for best results.

In addition to writing a stellar MLOps developer job description, you also need to be well-versed in interviewing styles. Work with your team to prioritize diversity in your hires and get talent from a variety of sources. Use behavioral or technical interviews and real-life problem-solving scenarios to get a clear idea of a candidate’s abilities.

Common Interview Questions To Ask When You Are Looking To Hire an MLOps Developer

Interviewing candidates for heavy technical roles in IT is tough when you do not have a strong background in tech. If you collaborate with your management team, you will be able to design an interview session that includes thoughtful questions.

Here is one question to raise at some point: “How would you explain the stages of the MLOps pipeline?” Someone with experience and knowledge will give a detailed answer about the steps in the pipeline. They will describe data acquisition, machine learning models: model training, model evaluation, deployment and model evaluation.

A second question that should be part of your interview is: “How do you deploy machine learning models in production?” A candidate who knows what they need to about machine learning should discuss information about direct deployment, containerization or an automated deployment process with model serving platforms.

A third question to add to your list is: “How do you use collaborative tools with your team?” There are many different types of collaborative tools and software suites. Look for someone who has experience with the software your company uses or shows evidence of an ability to learn a new tool.

How To Find Freelance MLOps Developers for Hire

Having an MLOps engineer join your team could provide valuable insight into your company data and give you ideas for your future direction. The goal is to find MLOps developers who have the right combination of skills and knowledge related to your project.

Our list of sites to hire MLOps developers is an excellent resource for shortlisting freelance candidates. You should also go beyond the sites by checking your in-person network, recruiting from colleges and reaching out to your competitors. One of your best and easiest options for hiring remote workers is by using Toptal, a top-notch source of vetted pros in IT.

The MLOps field is full of incredible talent. The challenge is finding the right person for your project. With this guide, you can hire strong contractors and unlock the potential for maximizing your machine learning projects.