Machine Learning Software Engineer Salary in United States during 2023

Salary details

The average Machine Learning Software Engineer salary lies between USD 145,000 and USD 217,600 in the United States. 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.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Top 20 Job Tags for Machine Learning Software Engineer roles

The three most common job tag items assiciated with Machine Learning Software 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 | 17 jobs Python | 16 jobs Engineering | 13 jobs Computer Science | 12 jobs ML models | 10 jobs PyTorch | 8 jobs TensorFlow | 7 jobs Architecture | 7 jobs APIs | 7 jobs PhD | 6 jobs Statistics | 6 jobs Java | 6 jobs NLP | 5 jobs GPU | 5 jobs Testing | 5 jobs CUDA | 5 jobs Mathematics | 5 jobs Privacy | 5 jobs Computer Vision | 4 jobs Research | 4 jobs

Top 20 Job Perks/Benefits for Machine Learning Software Engineer roles

The three most common job benefits and perks assiciated with Machine Learning Software Engineer job listings are Career development, Equity / stock options and Health care. 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 | 13 jobs Equity / stock options | 7 jobs Health care | 7 jobs Flex vacation | 6 jobs Competitive pay | 5 jobs Salary bonus | 5 jobs 401(k) matching | 4 jobs Startup environment | 4 jobs Parental leave | 3 jobs Medical leave | 3 jobs Flex hours | 2 jobs Team events | 2 jobs Relocation support | 2 jobs Wellness | 1 jobs Insurance | 1 jobs Home office stipend | 1 jobs Fertility benefits | 1 jobs

Salary Composition

The salary for a Machine Learning Software Engineer in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual achievements. In tech hubs like Silicon Valley, equity or stock options are common, providing employees with a stake in the company's success.

Regional differences can affect salary composition, with higher base salaries and bonuses often found in areas with a high cost of living, such as San Francisco or New York City. Industry also plays a role; for instance, finance and tech companies might offer more lucrative packages compared to academia or non-profits. Larger companies may provide more comprehensive benefits and bonuses, while startups might offer more equity to compensate for lower base salaries.

Increasing Salary

To increase your salary from a Machine Learning Software Engineer position, consider the following strategies:

• Specialization: Develop expertise in a niche area of machine learning, such as natural language processing or computer vision, which can make you more valuable to employers.
• Leadership Roles: Transition into roles with more responsibility, such as a team lead or manager, which often come with higher pay.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML, and consider pursuing advanced certifications or courses.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Machine Learning Software Engineer positions require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles involving complex research and development tasks. Advanced degrees can provide a deeper understanding of machine learning algorithms and data analysis techniques, making candidates more competitive.

Helpful Certifications

While not always required, certain certifications can enhance your credentials and demonstrate your expertise in machine learning and data science. Some popular certifications include:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications can validate your skills in specific platforms and tools, making you more attractive to potential employers.

Required Experience

Typically, employers look for candidates with at least 2-5 years of experience in software engineering, data science, or a related field. Experience with machine learning frameworks (such as TensorFlow, PyTorch, or Scikit-learn), programming languages (like Python, R, or Java), and data manipulation tools is crucial. Practical experience in deploying machine learning models and working with large datasets is also highly valued.

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