58 Machine Learning developers in 35 agencies found

AG
Machine Learning Engineer/Data Scientist and researcher with 20+ years of experience
Data scientist and researcher with a proven track record of developing and implementing large-scale algorithms that have significantly impacted business revenues and user experience of quite large ent...
2 Projects completed
GMT West Europe
All rates are indicative, annual rate includes 20% discount
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Updated: 12 Nov 2018
VD
Senior Data Scientist, Team Leader. Data Scientist with 11 years experience. PhD in Computer Science
A highly skilled Data Scientist with over 10 years of experience in data mining activities, data preparation, data analysis, and modeling. Vsevolod understands business's needs very well and has pract...
4 Projects completed
GMT West Europe
All rates are indicative, annual rate includes 20% discount
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Updated: 13 Nov 2018
All rates are indicative, annual rate includes 20% discount
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Updated: 14 Nov 2018
DS
All rates are indicative, annual rate includes 20% discount
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Updated: 10 Nov 2018
MB
All rates are indicative, annual rate includes 20% discount
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Updated: 13 Nov 2018
AM
All rates are indicative, annual rate includes 10% discount
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Updated: 09 Nov 2018

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Machine Learning Developer: 12 Must Have Technical Skills

Machine learning and artificial intelligence are now the most exciting and challenging domains of information technology. Machine learning requires results that are as exact as possible, so machine learning engineers should be able to think logically and be familiar with complex mathematical calculations. Below you can find a list of other technical skills that are typically required from machine learning developers.

12 Key Technical Skills to Help You Choose a Professional Machine Learning Engineer

  1.   Understanding of data structures, such as stacks, arrays, trees, graphs, queues, etc.
  2.   Familiarity with computer architecture fundamentals, such as bandwidth, deadlocks, distributed processing, memory, cache, etc.
  3.   Hands-on experience with at least one of the following programming languages: Java, Python, R, Matlab, or C++.
  4.   Understanding of computability and complexity concepts, such as P vs. NP, NP-complete problems, big-O notation, approximate algorithms, etc.
  5.   Expertise in machine learning techniques and algorithms, such as Naive Bayes, K-means, regression, decision tree, ANN, support vector machine, neural networks, or maximum entropy algorithms.
  6.   Knowledge of Unix tools, such as awk, cat, cut, find, grep, sed, sort, tr, and so on (because the machine learning activities are typically carried out in a Linux environment).
  7.   Familiarity with big data database tools, such as Hadoop. Ability to create distributed applications by using Hadoop and other solutions.
  8.   Knowledge of probability and statistics, because the machine learning algorithms are usually derived from statistical models and predictions.
  9.   Understanding of data science project lifecycle, data acquisition, and data collection.
  10.   Proficiency in software design, such as web APIs, static and dynamic libraries, etc.
  11.   Knowledge of advanced signal processing techniques.
  12.   Understanding of data modeling and evaluation.

In addition to technical (hard) skills, machine learning engineers should also demonstrate a range of soft skills, such as intellectual curiosity, analytical thinking, decision-making, proactivity, and strong communication skills.

To sum up, because there is a high demand for machine learning developers nowadays, we wish you good luck in finding a perfect candidate for your project before someone else finds them.