Salary for Senior-level / Expert Platform Engineer in United States during 2024

Salary details

The average senior-level / expert Platform Engineer salary lies between USD 137,400 and USD 240,000 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: Dec. 22, 2024

Top 20 Job Tags for Senior-level / Expert Platform Engineer roles

The three most common job tag items assiciated with senior-level / expert Platform Engineer job listings are Python, Engineering 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:

Python | 294 jobs Engineering | 290 jobs Machine Learning | 249 jobs AWS | 230 jobs Computer Science | 197 jobs Kubernetes | 193 jobs Architecture | 189 jobs Security | 174 jobs Terraform | 172 jobs Pipelines | 166 jobs Azure | 154 jobs CI/CD | 142 jobs DevOps | 134 jobs GCP | 125 jobs Docker | 121 jobs APIs | 106 jobs MLOps | 99 jobs Agile | 99 jobs Spark | 98 jobs SQL | 91 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Platform Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Platform Engineer job listings are Career development, Equity / stock options 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 | 258 jobs Equity / stock options | 132 jobs Flex hours | 131 jobs Health care | 118 jobs Team events | 93 jobs Medical leave | 84 jobs Parental leave | 82 jobs Startup environment | 72 jobs Competitive pay | 71 jobs Flex vacation | 70 jobs Salary bonus | 67 jobs Insurance | 56 jobs Wellness | 51 jobs Transparency | 36 jobs Home office stipend | 29 jobs 401(k) matching | 21 jobs Gear | 13 jobs Fitness / gym | 12 jobs Relocation support | 12 jobs Unlimited paid time off | 12 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Platform Engineer in AI/ML/Data Science typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually make up about 10-20%. Additional remuneration, such as stock options or equity, can vary significantly depending on the company size and industry. For instance, tech giants and startups in regions like Silicon Valley might offer substantial equity packages, whereas companies in other regions or industries might focus more on cash bonuses.

Increasing Salary Further

To increase your salary beyond the median of USD 176,750, consider the following strategies:

• Specialization: Develop expertise in niche areas within AI/ML, such as natural language processing, computer vision, or reinforcement learning, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Engineering or Chief Technology Officer, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML, and consider pursuing advanced certifications or degrees.
• Networking: Engage with professional networks and communities to discover new opportunities and negotiate better offers.
• Consulting: Explore consulting roles or freelance opportunities, which can offer higher hourly rates and flexibility.

Educational Requirements

Most Senior-level Platform Engineer positions 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 roles that involve complex problem-solving and research. Advanced degrees can provide a deeper understanding of machine learning algorithms, data structures, and statistical methods, which are crucial for this role.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials 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
• TensorFlow Developer Certificate

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

Required Experience

Typically, a Senior-level Platform Engineer in AI/ML/Data Science is expected to have at least 5-10 years of experience in software engineering, data science, or a related field. This experience should include a strong background in programming languages such as Python, Java, or C++, as well as hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Experience in deploying and managing AI/ML models in production environments is also highly valued.

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