Salary for Mid-level / Intermediate Machine Learning Platform Engineer in United States during 2024

Salary details

The average mid-level / intermediate Machine Learning Platform Engineer salary lies between USD 150,000 and USD 233,840 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: Nov. 17, 2024

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

The three most common job tag items assiciated with mid-level / intermediate Machine Learning Platform Engineer job listings are Machine Learning, Python and Distributed Systems. 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:

Machine Learning | 5 jobs Python | 4 jobs Distributed Systems | 4 jobs Linux | 3 jobs Research | 3 jobs Computer Science | 3 jobs TensorFlow | 2 jobs PyTorch | 2 jobs GPU | 2 jobs Engineering | 2 jobs CUDA | 2 jobs HPC | 2 jobs Mathematics | 2 jobs Deep Learning | 1 jobs NLP | 1 jobs Big Data | 1 jobs AWS | 1 jobs Rust | 1 jobs Testing | 1 jobs GCP | 1 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Machine Learning Platform Engineer job listings are Career development, Health care and Lunch / meals. 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 | 5 jobs Health care | 3 jobs Lunch / meals | 2 jobs Wellness | 2 jobs Team events | 2 jobs Salary bonus | 2 jobs Equity / stock options | 1 jobs Flex hours | 1 jobs Flex vacation | 1 jobs Startup environment | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Machine Learning Platform Engineer typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Performance bonuses can vary significantly, often comprising 10% to 20% of the total compensation, depending on the company's performance and individual contributions. Additional remuneration, such as stock options, can be a significant part of the package, particularly in startups or large tech firms, and may account for 10% to 20% of the total compensation. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher equity components, and industry, with finance and healthcare sectors sometimes offering higher bonuses. Company size also plays a role, with larger companies often providing more structured bonus and equity packages.

Increasing Salary Further

To increase your salary further from this position, consider pursuing advanced roles such as Senior Machine Learning Engineer, Machine Learning Architect, or transitioning into management positions like AI/ML Team Lead or Director of Machine Learning. Enhancing your technical skills in emerging areas such as deep learning, reinforcement learning, or AI ethics can also make you more valuable. Networking within the industry, attending conferences, and contributing to open-source projects can increase your visibility and open up higher-paying opportunities. Additionally, pursuing further education, such as a master's or Ph.D. in a relevant field, can also lead to higher salary prospects.

Educational Requirements

Most Mid-level/Intermediate Machine Learning Platform Engineer positions require at least a bachelor's degree in computer science, data science, mathematics, statistics, or a related field. However, many employers prefer candidates with a master's degree or higher, especially for roles that involve complex problem-solving and advanced algorithm development. A strong foundation in mathematics, particularly in linear algebra, calculus, and probability, is essential, along with proficiency in programming languages such as Python, R, or Java.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise. Certifications such as the Google Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, and Microsoft Certified: Azure AI Engineer Associate are well-regarded in the industry. These certifications validate your skills in deploying machine learning models on cloud platforms, which is a valuable asset for many employers.

Required Experience

Typically, a Mid-level/Intermediate Machine Learning Platform Engineer is expected to have 3 to 5 years of experience in the field. This experience should include hands-on work with machine learning models, data preprocessing, and deployment of models in production environments. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn is often required, along with familiarity with cloud platforms like AWS, Google Cloud, or Azure.

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