Platform Engineer Salary in 2024

Salary details

The average Platform Engineer salary lies between USD 128,000 and USD 227,000 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. 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 | 418 jobs Python | 410 jobs Machine Learning | 319 jobs AWS | 303 jobs Computer Science | 261 jobs Architecture | 260 jobs Security | 258 jobs Kubernetes | 255 jobs Azure | 232 jobs Pipelines | 226 jobs Terraform | 201 jobs DevOps | 201 jobs CI/CD | 195 jobs Agile | 174 jobs GCP | 170 jobs Java | 145 jobs Docker | 142 jobs Spark | 131 jobs SQL | 128 jobs APIs | 124 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 Equity / stock options. 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 | 389 jobs Health care | 179 jobs Equity / stock options | 163 jobs Flex hours | 162 jobs Startup environment | 129 jobs Team events | 117 jobs Competitive pay | 109 jobs Salary bonus | 103 jobs Medical leave | 99 jobs Parental leave | 91 jobs Flex vacation | 91 jobs Insurance | 78 jobs Wellness | 66 jobs Transparency | 44 jobs Home office stipend | 38 jobs 401(k) matching | 22 jobs Gear | 18 jobs Fitness / gym | 18 jobs Relocation support | 18 jobs Flexible spending account | 15 jobs

Salary Composition

The salary for a Platform Engineer in AI/ML/Data Science typically consists of a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly based on the region, industry, and company size. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, companies in regions with a lower cost of living might offer a smaller base salary but compensate with generous bonuses or stock options. Large tech companies often provide substantial equity packages, while startups might offer more in stock options to attract talent. Industries like finance or healthcare might offer higher bonuses compared to traditional tech companies.

Increasing Salary

To increase your salary from the current position, consider the following steps:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools relevant to AI/ML and data science.
• Advanced Education: Pursue advanced degrees or specialized certifications that can set you apart.
• Leadership Roles: Aim for leadership or managerial roles that come with higher pay scales.
• Networking: Build a strong professional network to learn about higher-paying opportunities.
• Negotiation: Improve your negotiation skills to better advocate for salary increases during performance reviews or when switching jobs.

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. can be advantageous, especially for roles that require deep technical expertise or research capabilities. Some positions might also value interdisciplinary studies that combine computer science with fields like statistics or data analysis.

Helpful Certifications

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

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

These certifications demonstrate a validated level of expertise and commitment to the field, which can be attractive to employers.

Required Experience

Typically, a Platform Engineer in AI/ML/Data Science is expected to have 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 often crucial. Additionally, hands-on experience with large-scale data processing and familiarity with AI/ML algorithms can be highly beneficial.

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