Salary for Mid-level / Intermediate Machine Learning Model Engineer during 2024

Salary details

The average mid-level / intermediate Machine Learning Model Engineer salary lies between USD 230,000 and USD 280,000 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 Mid-level / Intermediate Machine Learning Model Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Machine Learning Model Engineer job listings are Python, Machine Learning and Big Data. 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 | 1 jobs Machine Learning | 1 jobs Big Data | 1 jobs TensorFlow | 1 jobs PyTorch | 1 jobs Kafka | 1 jobs Spark | 1 jobs SQL | 1 jobs AWS | 1 jobs Research | 1 jobs Data Mining | 1 jobs Engineering | 1 jobs Flink | 1 jobs MLOps | 1 jobs PhD | 1 jobs ML models | 1 jobs Mathematics | 1 jobs Computer Science | 1 jobs NeurIPS | 1 jobs ICLR | 1 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Machine Learning Model Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Machine Learning Model Engineer job listings are Career development. 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 | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Machine Learning Model Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the compensation package is composed of:

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In tech hubs like Silicon Valley, New York, or Seattle, the base salary might be higher compared to other regions due to the cost of living and demand for talent.

• Bonus: Bonuses can be performance-based or company-wide and are often a percentage of the base salary. In larger tech companies, bonuses can be substantial, reflecting both individual and company performance.

• Equity/Stock Options: Particularly in startups and large tech firms, equity can be a significant part of the compensation package. This aligns the employee's interests with the company's success and can be a lucrative component if the company performs well.

• Other Benefits: These may include health insurance, retirement plans, and other perks like wellness programs, transportation allowances, or educational reimbursements.

Increasing Salary

To increase your salary from this position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing a master's or Ph.D. in a relevant field can open doors to higher-level positions and salary brackets.

• Leadership Roles: Transitioning into roles that involve team leadership or project management can lead to higher compensation.

• Networking and Industry Engagement: Attend conferences, contribute to open-source projects, and engage with the AI/ML community to increase your visibility and opportunities.

Educational Requirements

Most mid-level machine learning roles require at least a bachelor's degree in a relevant field such as computer science, data science, mathematics, or engineering. However, many employers prefer candidates with a master's degree or higher, especially for more technical or research-focused positions.

Helpful Certifications

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

• TensorFlow Developer Certificate: Demonstrates proficiency in building and deploying machine learning models using TensorFlow.

• AWS Certified Machine Learning – Specialty: Validates expertise in using AWS services for machine learning.

• Microsoft Certified: Azure AI Engineer Associate: Focuses on using Azure services for AI solutions.

• Google Professional Machine Learning Engineer: Covers designing, building, and productionizing ML models on Google Cloud.

Required Experience

Typically, a mid-level machine learning engineer is expected to have 3-5 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in deploying models to production and working in cross-functional teams is also highly valued.

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