Machine Learning Engineer Salary in Australia during 2023

Salary details

The average Machine Learning Engineer salary lies between USD 207,500 and USD 287,500 in Australia. 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

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 jobs

Top 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 jobs

Salary Composition for Machine Learning Engineers in Australia

The salary for a Machine Learning Engineer in Australia typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the bulk of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and the individual's contribution to projects. In larger tech companies or startups, equity or stock options are often included as part of the compensation, providing long-term financial benefits. The composition can vary by region, with major cities like Sydney and Melbourne offering higher salaries due to the cost of living and demand for tech talent. Industry also plays a role; for instance, finance and tech sectors tend to offer more competitive packages compared to academia or smaller enterprises.

Steps to Increase Salary from a Machine Learning Engineer Position

To increase your salary beyond the current position, consider the following strategies:

• Specialization: Develop expertise in niche areas of machine learning, such as deep learning, natural language processing, or computer vision, which are in high demand.
• Leadership Roles: Transition into roles that involve leading teams or projects, such as a Machine Learning Team Lead or Manager, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest advancements in AI/ML through courses, workshops, and conferences. This not only enhances your skills but also increases your value to employers.
• Networking: Build a strong professional network within the industry. Engaging with industry leaders and participating in relevant forums can open up opportunities for higher-paying roles.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements for Machine Learning Engineers

Most Machine Learning Engineer positions require at least a bachelor's degree in a related field such as Computer Science, Data Science, Mathematics, or Statistics. However, a master's degree or Ph.D. is often preferred, especially for roles involving complex research and development tasks. Advanced degrees provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for high-level positions.

Helpful Certifications for Machine Learning Engineers

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications validate your skills in using specific platforms and tools, which can be advantageous in job applications and salary negotiations.

Experience Requirements for Machine Learning Engineers

Typically, employers look for candidates with at least 2-5 years of experience in machine learning or related fields. This experience should include hands-on work with machine learning models, data preprocessing, and deployment of ML solutions. Experience in software development, data analysis, and familiarity with programming languages like Python and R is also highly valued. For senior roles, more extensive experience, including project management and team leadership, is often required.

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