- Engage directly with customers on MLOps platform or open source library at scale, playing a critical role in our mission delivering a ground-breaking solution to the market
- Work with the sales, product, engineering, support, and marketing teams for use case discovery, evangelism, and oftentimes teaching the product to new users
- Build relationships with them and engage by presenting product roadmaps and executive briefings, running QBRs, managing escalations, and conducting regular status calls
- Strategize and identify new use cases to grow accounts; find areas where FedML can provide the most value to increase renewals
- Engage with the product team to guide customer requests and establish our roadmap
- Work with the technical support team and other core FedML engineering teams to ensure that customer requests and escalations are resolved
- Identify and achieve targets on renewal rates, customer satisfaction, expansions, upsells, and new opportunities in assigned accounts
- Develop FedML champions and produce customer references for the marketing team
- Experience working in customer-facing technical roles (in customer success, consulting, or related discipline)
- A fast thinker and executor, have great communication skills, patient, a people’s person, sharp and details oriented.
- Experience at a SaaS, edge/cloud architectures, AI, web3/blockchain
- Bachelor’s degree in computer science or related field
- Programming language: Python; good knowledge in machine learning and AI
- Background in machine learning or working with ML tools and services, especially MLOps and large-scale data pipeline.
- Domain experience in sectors such as Healthcare, Life Sciences, FinTech, InsureTech, Manufacturing, IoT, Retail, Internet, Transportation, Communication and Media experience, etc.
- Some travel may be involved depending on customer’s needs
About the job
FedML, Inc. (https://fedml.ai) aims to provide an end-to-end machine learning operating system for people or organizations to transform their data to intelligence with minimum efforts. FedML stands for “Fundamental Ecosystem Development/Design for Machine Learning” in a broad scope, and “Federated Machine Learning” in a narrow scope. At the current stage, FedML is developing and maintaining a machine learning platform that enables zero-code, lightweight, cross-platform, and provably secure federated learning and analytics. It enables machine learning from decentralized data at various users/silos/edge nodes, without the need to centralize any data to the cloud, hence providing maximum privacy and efficiency. It consists of a lightweight and cross-platform Edge AI SDK that is deployable over edge GPUs, smartphones, and IoT devices. Furthermore, it also provides a user-friendly MLOps platform to simplify decentralized machine learning and real-world deployment. FedML supports vertical solutions across a broad range of industries (healthcare, finance, insurance, smart cities, IoT, etc.) and applications (computer vision, natural language processing, data mining, and time-series forecasting). Its core technology is backed by more than 3 years of cutting-edge research of its co-founders, who are recognized leaders in the federated machine learning community. Recently, FedML has raised around 2 million USD to scale up the product and engineering team.
FedML’s researchers and software engineers develop the next-generation platform for machine learning and artificial intelligence. We’re looking for researchers or engineers who bring fresh ideas from all areas, including machine learning and its applications in compute vision, natural language processing, data mining, as well as large-scale system design and implementation for distributed/cloud computing/systems, security/privacy, mobile/IoT systems, networking, Web UI design and development. As a software engineer, you will work on a specific project critical to our customers’ needs. We hope our engineers to be a faster learner and be enthusiastic to tackle new problems as we continue to push technology forward. You will design, develop, test, deploy, maintain, and enhance software solutions.
CEO – Salman Avestimehr
Salman Avestimehr is a world-renowned expert in federated learning with more than 20 years of R&D leadership in both academia and industry. He has been a Dean’s Professor and the inaugural director of the USC-Amazon Center on Trustworthy Machine Learning at University of Southern California. He has also been an Amazon Scholar in Amazon. He is a United States Presidential award winner for his profound contributions in information technology, and a Fellow of IEEE. https://www.avestimehr.com/
CTO – Chaoyang He
Chaoyang He is PhD from the CS department at the University of Southern California, Los Angeles, USA. He has research experience on distributed/federated machine learning algorithms, systems, and applications, and published papers at top-tier conferences such as ICML, NeurIPS, CVPR, ICLR, AAAI, and MLSys. He also has rich experience in industry in the areas of distributed/cloud computing and mobile/IoT systems. He was an R&D Team Manager and Principal Software Engineer at Tencent, and also worked as researcher/engineer at Google, Facebook, Amazon, Baidu, and Huawei. He has received a number of awards in academia and industry. Homepage https://chaoyanghe.com
We prefer California, but we also support office in other states or work from home if necessary.