Backend Engineer Salary in United States during 2024

Salary details

The average Backend Engineer salary lies between USD 144,000 and USD 229,900 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 Backend Engineer roles

The three most common job tag items assiciated with Backend 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 | 391 jobs Engineering | 371 jobs Machine Learning | 345 jobs AWS | 246 jobs APIs | 246 jobs Computer Science | 240 jobs Architecture | 235 jobs Kubernetes | 217 jobs Docker | 188 jobs Java | 185 jobs Pipelines | 174 jobs Security | 155 jobs PostgreSQL | 154 jobs Testing | 151 jobs Research | 137 jobs GCP | 132 jobs Kafka | 115 jobs LLMs | 114 jobs Agile | 109 jobs Privacy | 109 jobs

Top 20 Job Perks/Benefits for Backend Engineer roles

The three most common job benefits and perks assiciated with Backend Engineer job listings are Career development, Startup environment and Health care. 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 | 355 jobs Startup environment | 175 jobs Health care | 162 jobs Equity / stock options | 157 jobs Flex hours | 136 jobs Competitive pay | 124 jobs Flex vacation | 95 jobs Parental leave | 88 jobs Team events | 79 jobs Salary bonus | 71 jobs Insurance | 67 jobs Medical leave | 61 jobs Home office stipend | 49 jobs Wellness | 37 jobs 401(k) matching | 30 jobs Gear | 28 jobs Unlimited paid time off | 26 jobs Transparency | 23 jobs Relocation support | 14 jobs Fitness / gym | 12 jobs

Salary Composition

In the United States, the salary composition for a Backend Engineer specializing in AI/ML/Data Science can vary significantly based on factors such as 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 or New York, 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. These can significantly increase total compensation, particularly if the company performs well.

Increasing Salary Further

To increase your salary beyond the median of USD 190,000, consider the following strategies:

• Specialize Further: Gain 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 roles with more responsibility, such as a team lead or engineering manager, which typically come with higher pay.

• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. This can involve taking advanced courses or attending industry conferences.

• Networking: Build a strong professional network. Engaging with industry leaders and peers can open up opportunities for higher-paying positions.

Educational Requirements

Most positions for a Backend Engineer 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 involve complex algorithm development or research.

Helpful Certifications

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

• Certified Machine Learning Professional (CMLP): Validates your expertise in machine learning concepts and applications.

• AWS Certified Machine Learning – Specialty: Demonstrates your ability to design, implement, and maintain machine learning solutions on AWS.

• Google Professional Machine Learning Engineer: Shows proficiency in designing, building, and productionizing ML models using Google Cloud technologies.

Required Experience

Typically, companies look for candidates with 3-5 years of experience in software development, with a focus on backend engineering. Experience in AI/ML projects, either through work or personal projects, is highly valued. Familiarity with programming languages such as Python, Java, or C++, and frameworks like TensorFlow or PyTorch, is often required.

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