Key Skills to Look, Before Hire Freelance Machine Learning Engineers.

Here are some skills to look before hiring a Freelance Machine Learning Engineers: 

• Proven experience as a Machine Learning Engineer
• Understanding of data structures, data modeling and software architecture
• Deep knowledge of Math, probability, statistics and algorithms 
• Ability to write robust code in Python, Java and R 
• Familiarity with machines learning frameworks and libraries. 
• Excellent communication skills
• Ability to work in a team. 
• Outstanding analytical and problem-solving skills. 

Roles and Responsibilities of Machine Learning Engineers?

Here are some Roles and Responsibilities of Machine Learning Engineers: 

• Study and transform data science prototypes. 
• Design machine learning systems 
• Research and implement learning appropriate ML algorithms and tools.
• Develop machine learning applications according to requirements 
• Select appropriate datasets and data representation methods. 
• Run machine learning tests and experiments 
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary 
• Extend existing ML libraries and frameworks 
• Keep abreast of development in the field. 

What are the Interview questions for Machine Learning Engineers?

Here are some of the Interview Question for Machine Learning Engineers: 

1. What is Semi-supervised Machine Learning?
2. How do you choose an algorithm to use for a dataset?
3. Explain the K Nearest Neighbour Algorithm. 
4. What is Feature Importance in Machine Learning, and how do you determine it?
5. Is it true that we need to scale our feature values when they vary greatly?
6. The model you have trained has a low bias and high variance. How would you deal with it?
7. Which cross-validation technique would you suggest for a time-series dataset and why?

How to Hire the Best Freelance Machine Learning Engineers?

1. Set your goals- you should identify your goals you want them to achieve. This will help you determine what type of Machine Learning Engineers you need and what qualifications they should have.
2. Identify your needs - the next step is to determine what your project needs from the Machine Learning Engineers. By gathering and knowing this information it will now help you to establish a list of potential candidates.
3. Research and Find Potential Candidates - once you understand your goals, target audience and desired outcomes, you can now start researching potential Machine Learning Engineers who will fit for the role and will make your project into success. 
4. Create a job posting that outlines the Scope of Work and Compensation - this is an additional step to finding a skilled Professional Machine Learning Engineer. You should write an appealing job posting to get noticed. 
5. Review Applications and Portfolios to Identify the Best Candidates - To ensure the best results, you should be able to take a thorough approach when reviewing applications, testimonials and portfolios. 
6. Schedule Interview - when you’ve gathered all the information you need from the candidates, you are now ready to schedule an interview with your top choices and it will allow you to get to know them better. 
7. Make a final decision and extend an offer - You can now make an offer to the chosen Machine Learning Engineer after careful consideration and thorough review. Making sure that the chosen Machine Learning Engineer best fits the role and will be able to help and contribute to the growth or your organisation. 

What Challenges will you face when hiring Machine Learning Engineers?

Here are some challenges you will face when hiring Machine Learning Engineers:

• Data acquisition and cleaning 
• Overfitting 
• Feature Engineering 
• Model Selection 
• Deployment 

How do you negotiate rates and terms with your freelance Machine Learning Engineers?

1. Do your Research - You should understand the market rates of Machine Learning Engineers, their level of expertise and the type of project they require. Every different expertise demands different pay rates. This will always give you a good starting point for negotiations. 
2. Set a Budget - You should have a clear budget in mind based on the existing skills, experience and knowledge of a Machine Learning Engineer. This will help them stay within your financial limits while still providing fair compensation. 
3. Focus on Value, not Price - you should always consider the value a Machine Learning Engineers brings to their project instead of focusing on the cost. High quality may cost much, but it can always deliver better results, saving time and money in the long run, 
4. Be clear about your requirements - you should clearly outline the scope of work, deadlines, content guidelines and any added expectations. This will help Machine Learning Engineers to understand your expectations and allow them to provide more accurate information. 
5. Establish Long-Term Relationships - you should be able to offer more work or even bring them on full-time. This can provide Machine Learning Engineers more stable income. 
6. Make payment terms clear - when discussing agreement on rates, client’s should also discuss other things such as payments platforms, upfront payments, milestone payments and payment upon completion. Machine Learning Engineers may be more willing to negotiate rates if the payment terms are clear and well discussed.