Salary for Mid-level / Intermediate Backend Engineer in United States during 2024

Salary details

The average mid-level / intermediate Backend Engineer salary lies between USD 140,000 and USD 182,000 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 Mid-level / Intermediate Backend Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Backend Engineer job listings are Python, Machine Learning and Engineering. 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 | 68 jobs Machine Learning | 55 jobs Engineering | 52 jobs AWS | 49 jobs Computer Science | 43 jobs APIs | 38 jobs Docker | 35 jobs Architecture | 34 jobs Security | 33 jobs Kubernetes | 31 jobs PostgreSQL | 28 jobs Pipelines | 28 jobs Kafka | 26 jobs Java | 26 jobs GCP | 25 jobs SQL | 21 jobs Agile | 21 jobs Azure | 18 jobs Testing | 17 jobs Microservices | 16 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Backend Engineer job listings are Career development, Startup environment 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 | 59 jobs Startup environment | 30 jobs Equity / stock options | 27 jobs Competitive pay | 25 jobs Flex hours | 24 jobs Health care | 20 jobs Flex vacation | 17 jobs Parental leave | 16 jobs Medical leave | 12 jobs Salary bonus | 10 jobs Home office stipend | 9 jobs 401(k) matching | 6 jobs Gear | 6 jobs Transparency | 6 jobs Team events | 6 jobs Insurance | 6 jobs Wellness | 3 jobs Relocation support | 3 jobs Pet friendly | 3 jobs Unlimited paid time off | 3 jobs

Salary Composition

In the United States, the salary composition for a mid-level/intermediate backend engineer in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary package is divided into three main components:

• Base Salary: This is the fixed annual salary and usually constitutes the largest portion of the total compensation. In tech hubs like San Francisco, New York, or Seattle, the base salary might be higher due to the cost of living and competitive job market.

• Bonus: Bonuses can be performance-based or company-wide and are often paid annually. They can range from 10% to 20% of the base salary, depending on the company's performance and individual contributions.

• Additional Remuneration: This includes stock options, equity, or restricted stock units (RSUs), which are common in tech companies, especially startups. Larger companies might offer more substantial equity packages, which can significantly increase total compensation over time.

Increasing Salary Further

To increase your salary beyond the median of $175,000, consider the following strategies:

• Specialize in High-Demand Skills: Focus on acquiring expertise in niche areas of AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand.

• Pursue Leadership Roles: Transitioning into a lead or managerial position can significantly boost your salary. This might involve managing a team of engineers or leading a project.

• Continuous Learning and Certifications: Stay updated with the latest technologies and methodologies in AI/ML. Advanced certifications or a master's degree in a related field can make you more competitive.

• Networking and Industry Engagement: Attend conferences, workshops, and meetups to expand your professional network. Engaging with the community can open up opportunities for higher-paying roles.

Educational Requirements

Most mid-level/intermediate backend engineering roles in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for roles that involve complex data analysis and algorithm development.

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 your expertise in specific platforms and tools, making you more attractive to potential employers.

Required Experience

Typically, a mid-level/intermediate backend engineer in AI/ML/Data Science should have 3-5 years of relevant experience. This includes hands-on experience with programming languages like Python, Java, or Scala, and familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with data processing tools like Apache Spark or Hadoop is also beneficial.

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