Cloud Ace, Datatonic, Deloitte Consulting, Devoteam, Pandera Systems, Pythian Services and Quantiphi are among the 50-plus Google Cloud partners with employees who’ve already earned the cloud provider’s new Professional Machine Learning Engineer certification.
The certification, unveiled last week, validates cloud professionals’ expertise in designing, building and productionizing machine-learning (ML) models to solve business challenges using Google Cloud technologies, along with their knowledge of proven ML models and techniques.
Finding employees with the right ML skills has been among the top challenges for IT leaders this year, Google Cloud said.
The pre-pandemic tech talent shortage challenged many organizations’ digital transformations, and they’re now playing catch-up, according to a September report from staffing company Robert Half International that highlights IT industry trends and starting salaries that its recruiters expect to see next year.
“They are faced with the need to accelerate their transformation process as well as address technical debt within their organization,” the report said. “Many are seeking technology professionals with expertise in AI and machine learning, cloud computing and robotic process automation.”
Artificial intelligence (AI)/ML specialists are expected to have among the highest median starting salaries for non-executive IT jobs in the U.S. next year, according to the report.
When Ottawa’s Pythian Services heard earlier this year there potentially would be a new ML-related certification coming from Google Cloud, it put its ML team on notice and had them stand by to get it done, according to Vanessa Simmons, vice president of business development for the cloud, data and analytics services company, a Google Cloud Premier Partner.
Pythian currently has two Google Cloud-certified Professional Machine Learning Engineers, with the goal of having its entire team certified. Carlos Timoteo, a Pythian data scientist and machine- learning engineer, has been working with Google Cloud, applying AI Platform, BigQuery and big data services to implement ML solutions for the company’s customers.
Timoteo took his first Google Cloud certification exam, the Google Cloud Professional Data Engineer, in 2017. Since then, he and his work colleagues and fellow data scientists in his circle have been waiting for a well-designed data scientist/ML certification, he said.
“The preparation was not too hard or long given my experience as a data scientist leveraging Google Cloud,” Timoteo said. “I used the provided preparation guide to identify the points I needed to study more to ace the exam, leveraging Google Cloud documentation, the Google Developer Machine Learning Crash Course and a couple books.”
The Google Cloud Professional Machine Learning Engineer certification exam has a big emphasis on engineering ML solutions, according to Timoteo. The data science portion of the exam is more focused on the technique than on the algorithm details, implementation and limitation, he said. Beginners should expect snippets of code in Python and SQL and should learn TensorFlow 2.x and its ecosystem and how to implement TensorFlow 2 on Google Cloud Platform (GCP) in production, he noted.
“The exam is a valuable tool in assessing if the exam taker is able to propose a solution that satisfies many requirements recurrent for a variety of solutions, in several industry verticals,” Timoteo said. “With this added experience, Google and our customers can trust in my team and myself to build the most elegant and suitable solution to satisfy their business demands leveraging Google products and best practices in the market.”
London-based Datatonic, Google Cloud’s 2019 Specialization Partner of the Year for AI and ML, has two employees who earned the new certification.
“The Google Cloud Professional Machine Learning Engineer certificate gives a valuable overview of production ML on Google Cloud Platform, particularly on designing solutions with ML best practices in mind, such as mitigating model bias and utilizing GCP tools to interpret model predictions,” said Julian West, a Datatonic data scientist. “This will be actionable for future projects with clients increasingly conscious of model bias and explainability in their ML projects.”
Three Deloitte Consulting Google Cloud practitioners have earned the new certification.
“Deloitte teamed with Google early on with unwavering commitment to the certification program given their market leadership in AI/ML,” said Tom Galizia, lead commercial partner for Deloitte Consulting‘s Alphabet/Google alliance. “[Google CEO Sundar Pichai] has stated Alphabet overall is an AI-first company, which is clearly reinforced with their broad and deep portfolio of AI/ML/analytics-based technologies at unprecedented cost curves and commitment to the democratization of AI/ML.”
The Google Cloud Professional Machine Learning Engineer certification requires a two-hour exam. The cloud provider recommends candidates have at least three years of industry experience, including one or more years designing and managing solutions using GCP. An ML engineer is proficient in model architecture, data pipeline interaction and metrics interpretation, and requires familiarity with application development, infrastructure management, data engineering and security, according to Google Cloud.
The certification exam evaluates candidates’ abilities to frame ML problems, develop ML models and architect ML solutions. It also assesses their abilities to automate and orchestrate ML pipelines, prepare and process data, and monitor, optimize and maintain ML solutions.
Google Cloud partners also can earn Expertises in AI and ML, including in Google Cloud AI and ML APIs, Contact Center AI, Document AI and Visual Intelligence. Quantiphi, SoftServe and SpringML are among the more than 90 partners with those Expertises.
Partners who earn a Google Cloud Specialization in Machine Learning signal the strongest level of Google Cloud ML proficiency and experience. Accenture, Atos, Deloitte Consulting, DoiT International, Quanitphi and Pythian have achieved those designations.