Brings nearly 20 years of experience to continue to drive market leadership and growth as the need for machine learning operationalization increases
SUNNYVALE, Calif., November 8, 2018 – ParallelM, the leader in MLOps (machine learning operationalization), today announced that it has hired Dan Darnell as Vice President of Marketing. In this role, Darnell will oversee the Company’s marketing strategy and execution with a focus on establishing the MLOps, or machine learning operationalization, category. Darnell will report directly to ParallelM’s CEO, Sivan Metzger.
“There is no one better suited to help accelerate our efforts in enabling businesses to optimize and scale their machine learning capabilities. Dan’s widespread marketing experience across various types of enterprise software – from CRM to multivariate testing, real-time personalization, and machine learning platforms – will play a major role in propelling our marketing efforts, and our company, forward,” said Metzger.
Darnell brings nearly 20 years of experience in marketing for numerous enterprise software technology companies. Before joining ParallelM, Darnell served as a marketing consultant at H2O.ai, an open source leader in artificial intelligence (AI), where he drove product, solution and industry marketing focused on the automated machine learning market.
Prior to H2O.ai, Darnell was the Vice President of Product Marketing for Talend, a global leader in cloud data integration solutions, where he managed a global team of 15 marketers across product, solution, technical and customer marketing. Before Talend, Darnell was the Vice President of Marketing and Product for Baynote, a leading personalization platform for the retail and travel industries. While at Baynote, he was part of the executive team that re-launched the company in 2014 with a revitalized product and then saw its successful acquisition in 2016. Darnell has also worked in marketing and product roles at Adchemy, Interwoven, Oracle and Siebel Systems.
“Machine learning has become an important tool for both small and large businesses, and many companies are falling behind the curve when it comes to scaling machine learning across their business,” said Darnell. “I’m impressed with what ParallelM has already achieved and look forward to being part of the team during this exciting time of growth for both the company and the industry,” he added.
Darnell is an MBA graduate of the Carnegie Mellon Tepper School of Business and holds a degree in architectural engineering from the University of Colorado at Boulder.
ParallelM is the first and only company completely focused on delivering machine learning operationalization (MLOps) at scale. ParallelM’s breakthrough MCenter™ solution is built specifically to power the deployment and management of machine learning pipelines in production, so that companies can scale machine learning delivery across their business applications. ParallelM’s approach is that of a single, unified MLOps solution that embeds best practice processes in technology, enabling collaboration across all ML stakeholders to unlock the business value of AI. To learn more, visit www.parallelm.com and mlops.org.
ParallelM and MCenter are trademarks of Parallel Machines, Inc. All other trademarks are the property of their respective registered owners. Trademark use is for identification only and does not imply sponsorship, affiliation, or endorsement.