If you have a background in data science and strong math and statistics skills, you’re a great problem solver, and you’re looking for a new career opportunity, a machine learning engineer is a great path to take.
A machine learning engineer develops AI software used in predictive models. They must have advanced computer programming and coding skills. They create algorithms that organize data through machine learning. Machine learning systems can be found in online searches, virtual assistants, translation apps, and chatbots. Machine learning engineers design the algorithms to generate accurate predictions.
As a machine learning engineer, you will need excellent communication and collaboration skills to meet with management and define machine learning objectives. You will be required to solve complex problems and optimize machine learning libraries and frameworks by performing tests and statistical analysis and interpreting results. Advanced skill using Python, Java, and R code writing is essential to succeed as a machine learning specialist.
Machine learning specialists work in a wide range of industries, developing the machine learning algorithms for widely used devices like Siri, Alexa, online chatbots, marketing bots, and more.
Sample job description
[Your Company Name] is hiring an amazing and experienced machine learning engineer who loves to innovate and will work hard to keep us on the cutting edge in our technology systems. You will be working with a team of employees on our technology team to make sure that we continue to grow as one of the top companies in the industry. We have a technology-based growth focus and want to continue to invest in our technical team to ensure that we stay current in our products and systems. If you are a team player, work well under pressure, and take pride in pushing to always be the best that you can be, then you will be set for success in this position. You will be tasked with not only developing machine learning technology but also maintaining it and troubleshooting it when there are issues. If this sounds like something you can handle and you are excited to grow with a top company, then this may be the perfect opportunity for you!
Typical duties and responsibilities
- Programming experience in Python and Java
- Study science prototypes
- Build and productionalize machine learning algorithms
- Evaluate machine learning systems
- Analyze statistics data
- Lead adoption and integration of new technologies to improve our machine learning development and production pipelines
- Enhance the accuracy of the software
- Meet with managers
- Collaborate with data scientists to improve tools
- Design machine learning systems and AI software
- Run tests and monitor prototypes
- Create prototypes and data sets
- Adjust model performance as needed
Education and experience
- Bachelor’s degree in computer science, machine learning, mathematics, engineering, or related field
- 2+ years experience required
Required skills and qualifications
- Exceptional statistics skill
- Proficient with AI tools
- Programming skills
- Integrity and drive
- Excellent verbal and written communication skills
- Time management skills
- Analytical skills
- Problem-solving skills
- Advanced math skills
- Software engineering skills
- Data science skills
- Certifications applicable to a machine learning engineer or related
- Master’s degree in computer science or related field
Typical work environment
Machine learning engineers typically have their own office space. When they aren’t in their office they are on the worksites doing their part or assisting other teammates. Most of the time, they collaborate with other engineers or professionals and work as a team.
Machine learning engineers work full time and a minimum of 40 hours a week, Monday through Friday. Depending on the current project or deadline requirement, they may work longer hours up to 50 hours or so.
There are many certifications available to machine learning engineers who are looking to bolster their resumes. Some of these include:
- Professional Certificate Program in Machine Learning and Artificial Intelligence by MIT. This certification is a short program for beginners entering this field. They are educated on machine learning algorithms.
- Machine Learning with Python Certification. This course covers the basics of machine learning. It provides a general overview of machine learning topics. The course duration is eight weeks long and is free.
- IBM Machine Learning Professional Certification. This certificate includes six courses covering the theoretical and practical aspects of machine learning.
- Harvard University Machine Learning Certification Course. This course typically takes eight weeks or so to complete. This course builds more knowledge on algorithms, techniques, and teaches you how to build a recommendation system.
In order to build a career as a machine learning engineer, you need to have a high school diploma or equivalent. Candidates will then need a bachelor’s degree, master’s degree, or Ph.D. in computer science, mathematics, machine learning, engineering, or a related field with a few years of experience to qualify. In order to succeed in this line of work, you have to be highly knowledgeable. Consequently, many candidates go on to get certifications applicable to machine learning engineers to enhance their knowledge. You need to have strong communication skills, problem-solving skills, time management skills, be driven, and be a team player. Machine learning engineers are needed in a variety of industries, like artificial intelligence, data science, automation, analytics, and computer programming.
US, Bureau of Labor Statistics’ job outlook
SOC Code: 15-1221
|Projected Employment in 2030||40,200|
|Projected 2020-2030 Percentage Shift||22% increase|
|Projected 2020-2030 Numeric Shift||7,200 increase|
Machine learning engineers are projected to grow 22% from now till 2030. As the demand for technology continues to grow, so does the demand for more engineers and scientists. ML engineers are needed in a variety of industries, like artificial intelligence, data science, automation, analytics, and computer programming.