Salary for Mid-level / Intermediate Platform Engineer during 2024

Salary details

The average mid-level / intermediate Platform Engineer salary lies between USD 107,957 and USD 175,100 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: Dec. 22, 2024

Top 20 Job Tags for Mid-level / Intermediate Platform Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Platform Engineer job listings are Python, Engineering and AWS. 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 | 117 jobs Engineering | 111 jobs AWS | 81 jobs Machine Learning | 72 jobs Security | 69 jobs Kubernetes | 61 jobs Agile | 60 jobs Architecture | 58 jobs Azure | 57 jobs DevOps | 57 jobs Pipelines | 55 jobs Computer Science | 54 jobs CI/CD | 54 jobs Java | 49 jobs Terraform | 45 jobs GCP | 40 jobs SQL | 38 jobs Linux | 36 jobs Spark | 33 jobs Docker | 33 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Platform Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Platform Engineer job listings are Career development, Health care and Startup environment. 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 | 109 jobs Health care | 56 jobs Startup environment | 39 jobs Equity / stock options | 35 jobs Flex hours | 34 jobs Competitive pay | 34 jobs Salary bonus | 31 jobs Team events | 28 jobs Insurance | 21 jobs Flex vacation | 20 jobs Medical leave | 17 jobs Wellness | 16 jobs Parental leave | 14 jobs Fitness / gym | 8 jobs Transparency | 7 jobs Relocation support | 7 jobs Home office stipend | 7 jobs Gear | 6 jobs Conferences | 5 jobs Unlimited paid time off | 5 jobs

Salary Composition

The salary for a Mid-level/Intermediate Platform Engineer in AI/ML/Data Science typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The fixed base salary is the largest component, often accounting for 70-80% of the total compensation package. Performance bonuses can vary significantly based on company performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can form a significant part of the total compensation, especially in regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of equity but compensate with higher base salaries or bonuses.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Platform Engineer or transitioning into specialized roles like AI Architect or Data Science Manager. Upskilling through continuous learning and obtaining advanced certifications can also enhance your value. Networking within the industry and seeking opportunities in high-demand regions or companies known for competitive compensation can be beneficial. Additionally, gaining expertise in emerging technologies or niche areas within AI/ML can make you a more attractive candidate for higher-paying roles.

Educational Requirements

Most mid-level platform engineering 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 higher in a specialized area such as data science, machine learning, or artificial intelligence can be advantageous and sometimes preferred by employers. A strong foundation in programming, algorithms, and data structures is essential, along with a good understanding of machine learning principles and data analysis techniques.

Helpful Certifications

Certifications can bolster your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

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

These certifications validate your skills in deploying and managing machine learning models and platforms, which are crucial for platform engineering roles in AI/ML.

Required Experience

Typically, a mid-level platform engineer role requires 3-5 years of experience in software engineering, data engineering, or a related field. Experience with cloud platforms (such as AWS, Azure, or Google Cloud), containerization technologies (like Docker and Kubernetes), and CI/CD pipelines is often expected. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or Scikit-learn) and data processing tools (like Apache Spark or Hadoop) is also beneficial.

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