Hire Machine Learning engineers
Forget exhausting sourcing and screening the wrong candidates. Hire fast and on budget—place a request, interview 1-3 curated engineers, and get the best one onboarded by next Friday. Full-time or part-time, with optimal overlap.
How to hire Machine Learning engineer through Lemon.io
Place a free request
Tell us about your needs
Interview the best
Onboard the chosen one
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Sourcing and vetting
Expert
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Arranging cooperation
Support and troubleshooting
Why hire Machine Learning engineers through Lemon.io?
Trying to hire dedicated Machine Learning engineers is like looking for a needle in a haystack. Your startup pulls leadership off important jobs to interview endless devs who don’t meet the criteria just to find the one dev that does. Hiring with Lemon.io, gives you access to a talent pool of vetted devs you can trust, so you can hire better, faster.
Hire faster
Cut over one hundred hours off your hiring time by skipping over unfit engineers to focus on vetted devs with exceptional skills.
Hire better
Jump into a talent pool of 1300+ engineers to hire machine learning engineers who are pre-vetted and ready to start working now.
Hire the right dev, guaranteed
If your dev doesn’t meet every single expectation and fits perfectly into your team, we’ll find you another free of charge.
FAQ about hiring Machine Learning engineers
How much does it cost to hire a Machine Learning еngineer?
The cost to hire a Machine Learning еngineer could be influenced by the different types of cooperation, so the rate for in-house workers and independent contractors varies.
The base pay for hiring a Senior Machine Learning engineer in the US, San Jose, ranges from $164K – $252K, according to GlassDoor. The additional pay is $61K – $114K per year.
Why is Machine Learning expensive?
Machine Learning is expensive because of different factors: hardware and electricity costs, data acquisition and processing, licensing fees and cloud services. Also, the impact on the expenses includes costs associated with experimentation and innovation.
Machine Learning requires high-quality specialists: data analysts, data engineers, machine learning engineers, and AI engineers, and these specialists need to pass various training and development programs to improve their skills and enhance their knowledge.
How many hours a week do Machine Learning engineers work?
A Machine Learning engineer who works on a full-time project usually spends 40 hours per week on their tasks. However the working hours could depend on the project: the tasks relevant to the role, the complexity of the project, the budget, and the timeline could have a crucial impact on the schedule.
How much should I charge for a Machine Learning project?
The average hourly rate for a Senior Machine Learning engineer’s contract in San Jose, US, ranges from $70 to $94, according to GlassDoor. The rate depends on various factors: seniority level, skill sets, and number of years of experience.
Why are Machine Learning engineers paid so much?
Machine Learning engineers are in high demand in the market because they contribute to development across various industries. This field requires highly skilled specialists with extensive knowledge of different aspects of the AI market and industry. Typically, machine learning engineers invest considerable time and budget in obtaining various certifications and improving their skills, which is reflected in their rates.
How much coding does a Machine Learning engineer do?
There are no exact requirements for how much coding a Machine Learning engineer does; it depends on the project, the size and number of specialists on the team, and their specific responsibilities.
Usually, they need to spend a significant amount of their working time coding. Machine Learning engineers do a significant amount of coding for model development, data processing, algorithms implementation, automation, integration and optimization.
Is Machine Learning high-paying?
Yes, Machine Learning is high-paying. The average hourly rate for a Senior machine learning engineer’s contract in San Jose, US, ranges from $70 to $94, according to GlassDoor. The rate depends on various factors: seniority level, skill sets, and number of years of experience.
Are Machine Learning engineers in high demand?
Machine Learning engineers are in high demand in the market because they contribute to development across various industries. The highest demand for machine learning engineers is concentrated in technology & IT, healthcare and pharmaceuticals, finance and banking, e-commerce and retail, and automotive and transportation.
What is the no-risk trial period for hiring Machine Learning engineers on Lemon.io?
A no-risk paid trial period with Lemon.io is up to 20 hours, during which you can use the option to assess how a Machine Learning engineer works on real tasks before signing up for a subscription.
Additionally, we would like to highlight that we have a zero-risk replacement guarantee. This means that if your lemon.io Machine Learning engineer misses deadlines or fails to meet expectations, we’ll offer to you a new remote Machine Learning engineer. We have never had to do this before because only 1% of top applicants can join our community, but we promise our client support could be more supportive than your family.
How much does a Machine Learning engineer cost per hour in the USA?
The hourly rate, which is the base pay without additional pay for direct hire, if you are looking for a Senior Machine Learning engineer in San Jose, USA, ranges from $70 to $94, according to GlassDoor. Additional pay is $35K – $65K per year.
Where can I find a Machine Learning engineer?
If you are currently looking for a Machine Learning Engineer for your project, you can check global hiring websites such as Glassdoor, Indeed, Dice, and LinkedIn. You need to create the job listing, check the CVs, and proceed with the candidates who have the skills and experience that are good for your project. Afterward, you need to make a large number of screening calls and hard skills interviews, choose the best candidate, and sign the contract with them.
Alternatively, you can ask for help from Lemon.io—we will deliver 2-3 pre-screened developers to your startup. Don’t spend money and your team’s time on job postings, screening calls, and technical interviews—we have done those tasks earlier and pre-screened Senior Machine Learning engineers for you. Just send us your requirements and project overview and meet the miraculous developers in 48 hours.
Can I hire a Machine Learning engineer in less than 48 hours through Lemon.io?
You can hire a Machine Learning engineer in 48 hours through Lemon.io. In 48 hours, our team will manually find you a Machine Learning engineer in our pre-screened community – the Machine Learning engineer’s skills will be relevant to your requirements and preferences.
All the Machine Learning engineers in our talent pool have passed a few vetting stages: VideoAsk, completion of their me.lemon profile, a screening call with our recruiters that includes various technical questions, and a technical interview with our technical interviewers.
Q&A about hiring Machine learning developers
- What are the basics of AI and Machine Learning?
- What exactly is Machine Learning?
- How do you ensure the scalability of Machine Learning models in large-scale applications?
- How do Machine Learning algorithms improve over time?
- What is the difference between ML and Deep Learning?
- What is the best language for Machine Learning?
- How does Machine Learning contribute to predictive analytics in business?
- What is the main purpose of Machine Learning?
- What is the difference between AI and ML?
- What kind of problems can Machine Learning solve?
- What are the most common challenges in training Machine Learning models?
- What are the key considerations when deploying Machine Learning models in production?
- Are Machine Learning and Data Science the same?
- What are examples of Machine Learning?
- What are the 3 types of Machine Learning?
Why should you hire Machine Learning engineers for remote roles?
You can hope that the out-of-work engineers in your backyard are the best available. Or, you can take off last decade’s seat belt and wade into a talent pool as deep as the ocean. Your startup deserves the best, so why constrain yourself?
Decrease office costs
Every in-house worker requires space – a desk, a computer, a place to meet. The list of costs goes on and on. With remote contractors, you free your startup from office costs.
Increase productivity
In-house managers can easily get caught up in driving activity instead of increasing output. Because remote workers are judged solely on output, they are more productive on average than in-house employees.
Decrease personnel costs
When you hire machine learning engineers for remote positions, you can look beyond devs living in inexpensive cities to find remote engineers who have a lower cost of living, and lower wage expectations.
Increase your talent pool
Even in Silicon Valley, the talent pool can constrain your choice of engineers. When you increase the breadth of your search, you expand your talent pool to embrace unlimited options.