The latest phenomenon in the job market today is the huge demand for machine learning engineers which is growing massively day by day. Did you know, artificial intelligence and machine learning jobs is seeing an annual growth rate of around 40%? This enormous growth is fuelling the need for machine learning experts.
Amongst these gigantic requirements for machine learning jobs, the role of AI/ML engineers is the most popular but many new job roles such as AI developer, data scientist, predictive analytics expert, data domain expert, software data engineer, data collection specialist, data product manager and so on have emerged. The swift emergence of new titles reflects the fact that AI/ML has become mainstream in many multinational and even smaller companies.
In this blog, we will be providing an overall perspective of machine learning jobs with specific focus on machine learning engineer roles and responsibilities. Also, we have collated for our readers what the industry looks for in an ML engineer and the key pointers to be noted while looking at the job description of AI/ML job roles. Now let’s deep dive.
What should you know while applying to machine learning jobs
If you have the passion or interest to seek a career in AI/ML, then here are two key aspects which you should be aware of –
1. Machine Learning Engineer Key Responsibilities
The key responsibilities include –
- Perform statistical analysis
- Fine tuning test results
- Train and retrain systems
- Work on frameworks
- Undertaking machine learning experiments and test
- Designing machine learning programs
- Developing deep learning systems to various use cases based on the business needs and
- Finally implementing suitable AI/ML algorithms
2. Machine Learning Jobs Skill Requirements
As an AI/ML engineer, the industry looks upon the following necessities from candidates.
- Ability to write code in Java and Python
- Knowledge on basics of math and probability
- Good understanding and strong knowledge in algorithms and statistics
- Appreciation of data modelling, software architecture and data structures and
- Past experience of working in frameworks in last job or internship
- Reasonable communication skills
- Working in teams
- Preferred degree in Computer Science, Mathematics or similar courses or fields
- Finally a demonstrated experience of working in Machine Leaning Jobs before is an added advantage
With this broader understanding, let’s now get to the key part of what should be specifically focused in the AI/ML job descriptions.
Artificial Intelligence / Machine Learning Job Descriptions
The key part in any machine learning jobs description is the mandatory section. Candidates often tend to ignore or consider the mandatory section lightly. It is critical for all the job aspirants to read the mandatory requirement to determine whether you fit for the AI/ML job and accordingly strengthen/tailor your resume. For example, some technical AI positions require Python expertise whereas others may only require R experience or a combination of both. Further, knowing Python as a data scientists would definitely improve your skill as an AI/ML engineer, this is because of the nature of simplicity of the language with vast libraries and resources.
Following are selected sample AI/ML job descriptions for popular ML job titles which we have collated from various industries and actual job postings to enable our readers to quickly understand mandatory requirements for machine learning engineers.
An Artificial Intelligence developer plays a key role in using algorithms and neural networks to build usable solutions for business.
Job description: Important responsibility is to design, develop, enhance and implement AI solutions.
Machine Learning Engineer Skills: AI, ML, NLP, REST APIs, libraries, frameworks, R, Pythons and C#.
Additional Skills: Design, development and deployment of cloud application.
A professional responsible for obtaining, examining and inferring data for business use.
Job description: Build data models and organize structured and unstructured data to interpret solutions.
Mandatory Skills: R and/or Python
Additional Skills: Data mining and NLP.
A professional responsible for working with neural networks, algorithms and associated tools to solve problems in business or technology.
Job description: To play a critical role in bridging the gap between software developers and actual field workers or scientists.
Mandatory Skills: Java, computer vision and script writing
Additional Skills: Past experience of coding and programming
AWS or Azure Data Scientist
A professional responsible for applying Azure’s learning techniques in business to train, calculate and implement models to solve problems.
Job description: Working closely with customers in translating their requirements or thoughts into solutions
Mandatory Skills: Hadoop, R and Python
Additional Skills: Prior experience of working with AWS or Azure and data science knowledge
AWS or Azure Machine Learning Engineer
An engineer responsible for using machine learning and use AI solutions for addressing business problems and offer customized solutions
Job description: Build out data models and create very large data sets
Mandatory Skills: 2+ years of experience of working in Azure or AWS services
Additional Skills: ML and data labelling
Lead Data Scientist
A senior level position in data engineering stream who is responsible for managing the data team, building models and planning projects for business. Key role is to improve business product or services by analysing the captured data.
Job description: Work on addressing client challenges and identifying opportunities for clients in AI/ML.
Mandatory Skills: Over 5+ years of experience working in end-to-end POC development and demonstrations. Critical high end knowledge in R and Python.
Additional Skills: Implementation expertise in ML models and specialized experience in NLP.
Machine Learning Scientist
A key position in industry, whose responsibility is to work closely with ML engineers and data engineers to develop scalable solutions for business.
Job description: Work on designing and developing new- generation machine learning tool and technologies to offer critical competitive advantage to business and industry.
Mandatory Skills: Demonstrated understanding in AI/ML algorithms, learning models and in-depth experience with Hadoop and Tensorflow.
Additional Skills: Experience in graphical models
With technology such as Machine learning and predictive analytics rewriting the profit-making scene, companies will definitely drive the mandate for more and more AI/ML professional jobs in India.
The obvious question now you might have is, “How can you improve my skills to meet the mandatory section of the job description? The path to success is very simple; you may just need to strengthen your current skillset, don’t let your background and previous work discourage you from pursuing a job in AI/ML.
There are many global online learning courses available for AI/ML. For instance, Springboard’s Machine Learning Career Track: Become an ML engineer in six months online learning program provides 1:1 mentoring by SMEs along with job guarantee to help you get your dream job regardless of the skillset which you possess now.