Platform Engineer Salary in United States during 2024

Salary details

The average Platform Engineer salary lies between USD 128,000 and USD 227,000 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: Nov. 17, 2024

Top 20 Job Tags for Platform Engineer roles

The three most common job tag items assiciated with Platform Engineer job listings are Engineering, Python and Machine Learning. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Engineering | 411 jobs Python | 404 jobs Machine Learning | 313 jobs AWS | 296 jobs Computer Science | 257 jobs Architecture | 255 jobs Security | 253 jobs Kubernetes | 249 jobs Azure | 231 jobs Pipelines | 223 jobs DevOps | 199 jobs Terraform | 196 jobs CI/CD | 192 jobs Agile | 174 jobs GCP | 169 jobs Java | 144 jobs Docker | 140 jobs Spark | 128 jobs SQL | 125 jobs APIs | 122 jobs

Top 20 Job Perks/Benefits for Platform Engineer roles

The three most common job benefits and perks assiciated with Platform Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 384 jobs Health care | 175 jobs Flex hours | 161 jobs Equity / stock options | 159 jobs Startup environment | 127 jobs Team events | 116 jobs Competitive pay | 106 jobs Salary bonus | 100 jobs Medical leave | 96 jobs Flex vacation | 89 jobs Parental leave | 88 jobs Insurance | 76 jobs Wellness | 65 jobs Transparency | 43 jobs Home office stipend | 38 jobs 401(k) matching | 19 jobs Gear | 18 jobs Fitness / gym | 17 jobs Relocation support | 17 jobs Unlimited paid time off | 15 jobs

Salary Composition for AI/ML/Data Science Platform Engineers

The salary for a Platform Engineer in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech-heavy regions like Silicon Valley. The base salary is often the largest component, accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company’s performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, can be a significant part of the package in startups or large tech companies, potentially adding another 10-20% to the total compensation.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies, financial services, and healthcare often offer higher salaries compared to academia or non-profit sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Steps to Increase Salary from This Position

To increase your salary from a Platform Engineer position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to AI/ML and data science. Specializing in niche areas like deep learning, natural language processing, or cloud-based AI solutions can make you more valuable.

• Advanced Education: Pursuing further education, such as a master's or Ph.D. in a related field, can open up higher-paying opportunities and leadership roles.

• Networking and Professional Visibility: Attend industry conferences, contribute to open-source projects, and publish articles or research papers. Building a strong professional network can lead to new opportunities and salary negotiations.

• Leadership Roles: Aim for leadership or managerial positions within your organization, as these roles typically come with higher compensation.

• Company Switch: Sometimes, moving to a different company, especially one that is scaling rapidly or offers better compensation packages, can result in a significant salary increase.

Educational Requirements

Most Platform Engineer roles in AI/ML/Data Science 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 positions involving complex problem-solving and research. Courses in machine learning, data structures, algorithms, and software engineering are particularly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Machine Learning Professional (CMLP)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate

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 3-5 years of experience in software engineering, data engineering, or a related field. Experience with cloud platforms, data pipelines, and machine learning frameworks is highly valued. Additionally, hands-on experience with AI/ML projects, either through previous employment or personal projects, is crucial.

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