Machine Learning Engineer Salary in United Kingdom during 2023
💰 The median Machine Learning Engineer Salary in United Kingdom during 2023 is USD 135,000
✏️ This salary info is based on 31 individual salaries reported during 2023
Salary details
The average Machine Learning Engineer salary lies between USD 92,280 and USD 200,000 in the United Kingdom. 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.
- Job title
- Machine Learning Engineer
- Experience
- all levels
- Region
- United Kingdom
- Salary year
- 2023
- Sample size
- 31
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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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:Salary trend
Top 20 Job Tags for Machine Learning Engineer roles
The three most common job tag items assiciated with Machine Learning Engineer job listings are Machine Learning, Python and Engineering. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:
Machine Learning | 1793 jobs Python | 1481 jobs Engineering | 1356 jobs Computer Science | 1038 jobs ML models | 1017 jobs PyTorch | 853 jobs TensorFlow | 782 jobs Research | 749 jobs Deep Learning | 730 jobs Pipelines | 703 jobs AWS | 651 jobs NLP | 610 jobs Statistics | 559 jobs Testing | 539 jobs Architecture | 529 jobs Mathematics | 462 jobs Java | 462 jobs SQL | 449 jobs Spark | 423 jobs GCP | 418 jobsTop 20 Job Perks/Benefits for Machine Learning Engineer roles
The three most common job benefits and perks assiciated with Machine Learning Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:
Career development | 1495 jobs Health care | 752 jobs Flex hours | 644 jobs Equity / stock options | 631 jobs Startup environment | 531 jobs Flex vacation | 524 jobs Salary bonus | 479 jobs Competitive pay | 419 jobs Team events | 401 jobs Parental leave | 391 jobs Insurance | 339 jobs Medical leave | 322 jobs Wellness | 256 jobs 401(k) matching | 195 jobs Home office stipend | 176 jobs Conferences | 134 jobs Unlimited paid time off | 118 jobs Relocation support | 92 jobs Signing bonus | 84 jobs Flexible spending account | 83 jobsSalary Composition for Machine Learning Engineers in the UK
The salary for a Machine Learning Engineer in the UK typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, pension contributions, and paid leave.
The composition can vary based on several factors:
- Region: Salaries in London and other major cities tend to be higher due to the increased cost of living and demand for tech talent.
- Industry: Industries like finance and technology often offer higher salaries compared to academia or public sector roles.
- Company Size: Larger companies may offer more comprehensive benefits and bonuses, while startups might offer equity as part of the compensation package.
Steps to Increase Salary from a Machine Learning Engineer Position
To increase your salary from a Machine Learning Engineer position, consider the following strategies:
- Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand.
- Pursue Advanced Education: Obtaining a master's or Ph.D. in a relevant field can open up higher-paying opportunities.
- Gain Leadership Experience: Transitioning into roles like a team lead or manager can significantly increase your earning potential.
- Negotiate Effectively: Develop strong negotiation skills to advocate for higher pay during performance reviews or when switching jobs.
- Expand Your Network: Engage with industry professionals through conferences, meetups, and online platforms to discover new opportunities.
Educational Requirements for Machine Learning Engineers
Most Machine Learning Engineer positions require at least a bachelor's degree in a relevant field such as computer science, mathematics, statistics, or engineering. However, many employers prefer candidates with a master's degree or Ph.D. due to the complex nature of the work. Advanced degrees often provide deeper knowledge and research experience, which are highly valued in this field.
Helpful Certifications for Machine Learning Engineers
While not always required, certain certifications can enhance your credentials and demonstrate expertise:
- Google Professional Machine Learning Engineer: Validates your ability to design, build, and productionize ML models on Google Cloud.
- AWS Certified Machine Learning – Specialty: Demonstrates your skills in building, training, and deploying ML models on AWS.
- Microsoft Certified: Azure AI Engineer Associate: Focuses on using Azure services to build AI solutions.
- TensorFlow Developer Certificate: Shows proficiency in using TensorFlow for machine learning and deep learning tasks.
Experience Requirements for Machine Learning Engineers
Typically, employers look for candidates with 2-5 years of experience in machine learning or related fields. This experience should include hands-on work with machine learning models, data analysis, and programming. Experience with specific tools and frameworks like TensorFlow, PyTorch, or scikit-learn is often required. Additionally, experience in software development and familiarity with cloud platforms can be advantageous.
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