What does a Machine Learning Engineer do?
Machine learning engineers are the designers of self-running software that brings machines the ability to automate models that are predictive. They work with data scientists to take information and feed curated data into the models that they've uncovered or discovered. They use theoretical models within the data science sphere and build them out to scale as functioning and productive units or models that handle terabytes of real-time data.
Machine learning engineers also function as a bridge or intersection for software engineering and data science. They use the available big data tools to improve programming frameworks and to gather raw data from pipelines. They redefine raw data into data science models that are ready to scale. Some machine learning engineers design the software programs that control technological tools, including computers or robots. They can develop algorithms that allow machines to identify trends or patterns in their programming data and as a self-contained unit, and a machine can then teach itself to understand commands, or even to think for itself. Machine learning engineers need a minimum of a bachelor’s degree in computer science or related fields.
- Message and reinforce the vision, purpose, and strategy of the team.
- Work with engineering leaders to transform research into AI capabilities in our platform.
- Develop text, image and video-analysis solutions for agents to leverage to grow their business.
- Serve as a tech lead on a team of applied and data scientists.
- Collaborate with data scientists, engineers, product teams and other key stakeholders and drive ML projects from conception to completion.
- Design, develop, validate, deploy, and manage new functionality of a cash flow forecasting solution.
- Develop and deliver client facing sales presentations at the C-suite Executives.
- Partner with QA team on test automation of new and existing functionalities.
- Collaborate with other engineers to conduct system integration and tests.
- Monitor and troubleshoot performance issues on the enterprise data pipelines.
- Work cross-functionally, to identify a business problem, design technical solutions, demonstrate, and deliver business impact.
- Work on deployment and ensure products are production-ready and function smoothly.
- Launch new products and features, test their performance, and iterate quickly.
- Work with a small team on cutting-edge research and development projects.
- Guide and mentor engineering teams to raise collective technical expertise.
- Define database structures, identify data type for collection, and setup data analysis software.
- Bachelor's or Graduate's Degree in computer engineering, electrical engineering, computer science or engineering, or equivalent experience.
- Fluency in applicable software, systems, and processes, such as SIRI, APIs, JAVA, and C.
- Experience with algorithm design and natural language processing.
- Comfortable working with big data, statistics, and frameworks.
Machine Learning Engineer Salaries
Average Base Pay
Machine Learning Engineer Career Path
Learn how to become a Machine Learning Engineer, what skills and education you need to succeed, and what level of pay to expect at each step on your career path.
Average Years of Experience
Machine Learning Engineer Insights
“I was given great resources to learn and buildup my skills and create projects that would help me apply my skills”
“Everyone is super helpful and was happy to teach and help me during my time here”
“Little / none salary raise and absolutely in the dark what it takes for that to happen.”
“3. One of the best engineering processes that integrates several cutting edge software development tools and best practices.”
“You will find better internships and job opportunities from people that will actually teach you and not exploit your effort.”
“The job security is sketchy at best which is one of the primary reasons I found a new job.”
“The work life balance couldn't be better (this might though be because of German employer laws).”
“It will be a really good opportunity to learn if you can grab an internship here.”
Machine Learning Engineer Interviews
Frequently asked questions about the role and responsibilities of machine learning engineers
Machine learning engineers delve into the field of artificial intelligence and design predictive algorithms. These algorithms make it easier for machine learning engineers to sift through huge data sets. During the typical day of a machine learning engineer, a machine learning engineer is constantly tweaking algorithms to make them more efficient. They run tests until the algorithm reaches optimum performance.
Machine learning engineering is a lucrative career. Most professionals can earn six-figure salaries. Analytical candidates are especially suited to become a machine learning engineer. It is also a good job for organized applicants with the focus to precisely analyze the effects of algorithm adjustments on data processing.
A machine learning engineer's average salary is approximately $6,000 per year, which makes machine learning engineering one of the top jobs in the U.S. Bonuses can bring that figure up to $9,975. Experience is a significant salary determinant in this career, and expert machine learning engineers earn significantly more than entry level applicants who have only just finished their education.
Machine learning engineering can be considered difficult, as there is certain tedium to some aspects of working as a machine learning engineer. The smallest mistake can affect the outcome of the entire data analysis process, which is a lot of pressure for some people. The strongest candidates will have strong concentration and focus.