Founded by Dr. Prasad Akella and Krishnendu Chaudhury, our portfolio company Drishti is transforming discrete manufacturing through a combination of AI-powered video analytics, data, and insights that helps humans on the factory floor work more efficiently with machines. Drishti’s mission is to “extend human potential in an increasingly automated world.”
Drishti uses computer vision and AI to create continuous streams of data and video from manual actions. The entire team, including line operators, is engaged in the process of using this data to produce improvements.
Drishti recently joined the Toyota AI Ventures portfolio as part of its $25M Series B round, and is now hiring for multiple engineering and marketing roles. If you are interested in facilitating the synergy between humans and technology in manufacturing, read on about two of the open roles currently available on the Toyota AI Ventures job board: product marketing manager and deep learning engineer.
Product Marketing Manager (Mountain View, California, or remote)
Drishti is looking for a product marketing manager who will communicate the benefits of its technology to the world’s largest manufacturers. This role is critical in shaping Drishti’s message to prospects and customers. You must have prior experience in the manufacturing space, and you should understand the perspective (and pain points) of discrete manufacturers in terms of quality, productivity training, and other assembly line challenges. The position is located in Mountain View, California, but working remotely is also possible.
In this role, you will be working cross-functionally with marketing, product, customer experience, and sales. You will develop content and campaign strategies that fit the customer, contribute to building out customer personas and buyer journeys, and recommend pricing and packaging strategies. You will create content (datasheets, white papers, sales enablement, etc.) and manage integrated marketing campaigns. Responsibilities also include competitive analysis, managing focus groups, and market segmentation.
In addition to manufacturing industry expertise, you need at least five or more years of experience in product marketing roles launching SaaS products, as well as familiarity with accounts-based marketing sales processes and marketing automation software. A proven understanding of enterprise buying cycles is also needed. The ideal candidate will also be a strong communicator, collaborator, and problem solver.
Deep Learning Engineer — Platform and Infrastructure (Bangalore, India)
The deep learning (DL) engineer for platform and infrastructure at Drishti will collaborate with other experts in DL and computer vision, with the goal of ensuring that data created by Drishti’s platform is delivered and used by major manufacturing companies. In this role, you will build and maintain large-scale systems to support the entire pipeline, which includes data collection, training, real-time inference of deep neural networks, and continuous improvement. Your duties will include optimizing neural networks, aiming for higher throughput and lower latencies.
You must have a bachelor’s degree in electrical engineering or computer science from a top tier engineering college. You must be fluent in C++ or Python, and have solid fundamentals in computer science, machine learning, and neural network fundamentals. A master’s degree or doctorate in machine learning or computer science (or equivalent work experience) is a bonus. You will also ideally have experience with DL libraries, DL and machine learning models, dataset pipelines, cloud platforms, and large scale distributed systems.
Drishti is additionally recruiting for a variety of engineering roles, and you can check out all of the jobs available on the Toyota AI Ventures jobs board. A number of our portfolio companies are also recruiting right now, so be sure to sign up for the Toyota AI Ventures Talent Network.
Enabling AI-Powered Production: Our Portfolio Company Drishti is Hiring was originally published in Toyota AI Ventures on Medium, where people are continuing the conversation by highlighting and responding to this story.