Customer Success Engineer

Location

Sunnyvale, CA | United States

Job description

Responsibilities

• 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

Minimum Qualifications

• 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. ( empowers our clients to build & scale any machine learning or artificial intelligence models anywhere. That includes the latest foundation models as well as more traditional ML models. Our products cover both training, serving with a low-code UI MLOPs & LLMOps platform. We also offer a Federated Machine Learning solution for cross-silo training for data privacy sensitive applications.

Our earliest products power federated machine learning missions for clients in several industries, where data privacy, low latency serving, and low cost of data storage are important to the client. Our easy-to-use FedML MLOps solution enables data science and machine learning engineering to work seamlessly together to deploy & manage their model to production machines. Our federated learning and serving solutions support siloed edge devices, smartphones, and IoT.

Our next generation of solutions includes geo-distributed machine learning and serving that continues our tradition of delivering easy-to-use, simple, low-cost, and enterprise grade MLOPs solutions. Our MLOps and evolving LLMOps platform will always empower experimentation, observability, evaluation, governance, and collaboration for our clients’ AI & ML training and serving needs, as well as other general computing needs.

FedML supports vertical solutions across a broad range of industries (healthcare, finance, insurance, automotive, advertising, 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.

FedML's researchers and software engineers and product teams are busy developing the next-generation FedML platform for machine learning and artificial intelligence and we're looking to grow our team with skilled professionals who bring fresh ideas from all areas, including machine learning and its applications, computer vision, natural language processing, large-scale system design, distributed/cloud computing/systems, MLOps, security/privacy, mobile/IoT systems, and networking. We’re an early stage startup, hence you will work on projects which are critical to our customers' and our business needs. If you love to learn, and love to convert ideas into real and scalable machine learning infrastructure products and applications, FedML may be a great place for you.

Location

Our HQ is in Sunnyvale California. Preference is for someone local who can be at our office regularly. Hybrid is ok.

How to apply

If you are interested, please apply via the link.

Job tags

Salary