Yesterday
51 - 200
Join Branch as a ML engineering intern to develop financial services.
July 25
51 - 200
Work on applied computer vision pipelines leveraging AI/ML methods.
June 3
11 - 50
🇺🇸 United States – Remote
💰 $6.7M Seed Round on 2021-11
👨🎓 Internship
⚪️ Entry-level
🤖 Machine Learning Engineer
February 2
10,000+
January 28
51 - 200
🇺🇸 United States – Remote
💵 $190k - $210k / year
💰 $27.5M Series B on 2020-12
⏰ Full Time
⚪️ Entry-level
🤖 Machine Learning Engineer
December 15, 2023
11 - 50
December 11, 2023
11 - 50
Artificial Intelligence • eHealth • Machine Learning
51 - 200
💰 $27.5M Series B on 2020-12
Wireless Access Points • Wi-Fi • Cloud-Managed Networking
11 - 50
The average salary for remote ml engineers is $177,351 per year. This is based on data from 1,422 job openings.
Our advanced AI searches the internet for remote job openings and posts them on our website. We use the salary data from these job postings to calculate machine learning engineer salaries.
Below is a breakdown of salary data by years of experience:
Experience | Number of roles analyzed | Average Salary |
---|---|---|
⚪️ Entry-level Machine Learning Engineer (0 yrs) | 6 | $173,333 |
🟢 Junior Machine Learning Engineer (1-2 yrs) | 47 | $125,098 |
🟡 Mid-level Machine Learning Engineer (2-4 yrs) | 382 | $161,831 |
🟠 Senior Machine Learning Engineer (5-9 yrs) | 808 | $177,523 |
🔴 Lead Machine Learning Engineer (10+ yrs) | 179 | $223,553 |
You need strong programming skills in Python or R, familiarity with machine learning libraries like TensorFlow or PyTorch, and a basic understanding of algorithms and data structures. Analytical thinking, problem-solving skills, and proficiency in data manipulation are also important.
Typically, a degree in computer science, data science, or a related field is required. However, completing relevant online courses or certifications in machine learning can also be advantageous, along with a portfolio showcasing projects or internships.
Responsibilities include assisting in the development of machine learning models, preprocessing and analyzing data, running experiments to optimize algorithms, and collaborating with senior engineers on various projects. Documentation and reporting findings are also part of the role.
Benefits include flexible working hours, reduced commuting, exposure to various industries, and the opportunity to work with cutting-edge technology. You'll also gain valuable experience that can lead to advancement in the rapidly growing field of AI and machine learning.