Salary for Entry-level / Junior Machine Learning Engineer during 2023

Salary details

The average entry-level / junior Machine Learning Engineer salary lies between USD 70,800 and USD 145,885 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 24, 2024

Salary trend

Top 20 Job Tags for Entry-level / Junior Machine Learning Engineer roles

The three most common job tag items assiciated with entry-level / junior Machine Learning Engineer job listings are Machine Learning, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Machine Learning | 181 jobs Python | 146 jobs Engineering | 107 jobs Computer Science | 103 jobs TensorFlow | 72 jobs PyTorch | 72 jobs Deep Learning | 70 jobs AWS | 68 jobs Research | 68 jobs ML models | 64 jobs Mathematics | 58 jobs Pipelines | 56 jobs SQL | 52 jobs Testing | 51 jobs NLP | 48 jobs Docker | 45 jobs Java | 43 jobs Consulting | 42 jobs GCP | 41 jobs Statistics | 40 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Machine Learning Engineer roles

The three most common job benefits and perks assiciated with entry-level / junior Machine Learning Engineer job listings are Career development, Team events and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 120 jobs Team events | 85 jobs Flex hours | 72 jobs Startup environment | 67 jobs Competitive pay | 58 jobs Health care | 43 jobs Conferences | 43 jobs Salary bonus | 38 jobs Equity / stock options | 37 jobs Travel | 16 jobs Flex vacation | 15 jobs Insurance | 15 jobs Medical leave | 13 jobs Wellness | 12 jobs Fitness / gym | 12 jobs Parental leave | 11 jobs Relocation support | 9 jobs 401(k) matching | 6 jobs Snacks / Drinks | 6 jobs Gear | 5 jobs

Salary Composition

The salary for an entry-level or junior machine learning engineer typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and the individual's performance. In tech hubs like Silicon Valley, companies might offer stock options as part of the compensation package, which can be a significant addition to the overall remuneration. The composition can also vary by region, with higher base salaries often found in areas with a higher cost of living. Industry and company size also play a role; larger tech companies or those in high-demand sectors like finance or healthcare may offer more competitive packages.

Increasing Salary

To increase your salary from an entry-level position, consider gaining more experience and expertise in specialized areas of machine learning, such as deep learning, natural language processing, or computer vision. Pursuing advanced degrees, such as a master's or Ph.D., can also open up higher-paying opportunities. Networking within the industry and seeking mentorship can provide insights into career advancement. Additionally, taking on leadership roles in projects or teams can demonstrate your capability to handle more responsibility, which can lead to promotions and salary increases. Staying updated with the latest technologies and trends in AI/ML can also make you more valuable to employers.

Educational Requirements

Most entry-level machine learning engineer positions require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. Some positions may prefer candidates with a master's degree, especially if the role involves more complex tasks or research components. A strong foundation in mathematics, particularly in linear algebra, calculus, and probability, is essential. Programming skills, especially in languages like Python and R, are also crucial. Understanding data structures and algorithms is often a key requirement.

Helpful Certificates

While not always mandatory, certain certificates can enhance your resume and demonstrate your commitment to the field. Certificates from recognized institutions or platforms, such as the "Machine Learning" course by Andrew Ng on Coursera, Google's TensorFlow Developer Certificate, or AWS Certified Machine Learning – Specialty, can be beneficial. These certifications can provide a structured learning path and validate your skills to potential employers.

Required Experience

For an entry-level position, employers typically look for candidates with some practical experience, which can be gained through internships, projects, or contributions to open-source projects. Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Familiarity with data preprocessing, model training, and evaluation techniques is also important. While extensive professional experience may not be necessary, demonstrating hands-on experience through a portfolio of projects can be advantageous.

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