Human Resources Manager
2 weeks ago
Job Description
Job Description
FedML is a leading ML and AI company that builds & delivers an open and collaborative AI infrastructure platform. FedML powers production workloads anywhere for a full range of models (including LLMs) on a range of compute options, including edge computing, distributed computing, multi-cloud, geo-distributed, and federated machine learning.
Responsibilities
Partners with the leadership team to understand, build and execute the organization's human resource and talent strategy particularly as it relates to current and future talent needs, recruiting, retention, and succession planning.
Manages the talent acquisition process, which may include recruitment, interviewing, and hiring of qualified job applicants, particularly for managerial, exempt, and professional roles; collaborates with departmental managers to understand skills and competencies required for openings.
Builds and continuously improves the compensation structure for different roles and levels.
Analyzes trends in compensation and benefits; researches and proposes competitive base and incentive pay programs to ensure the organization attracts and retains top talent.
Provides support and guidance to HR daily routine tasks and compliance requirements.
Provides support and guidance when complex, specialized, and sensitive questions and issues arise.
Minimum Qualifications
Bachelor's degree in Human Resources, Business Administration, or related field required.
A minimum of three years of human resource management experience.
Must have experience working in a startup environment.
Great communication skills.
Preferred Qualifications
Experience with AI startups is a big plus
Knowledge/experience
of AI technology
Enthusiastic self-starter, familiar with and able to adapt to fast-paced and ambiguous environmen
About the Job
FedML, Inc. (https:/fedml.ai) empowers our clients to have AI capabilities such as training anywhere, serving anywhere, from data anywhere. FedML is all about Foundation models at scale, covering all aspects of distributed training and serving, and includes a "Federated Machine Learning" solution option as well.
Our earliest products currently 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. These easy-to-use FedML MLOps solutions are also provably secure and empower lifting intelligence in use cases where the user data should not be centrally pooled. Our federated learning and serving solutions support siloed edge devices, smartphones, and IoT.
We’re currently building our next generation of solutions, which include 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.
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 follow the form here. Be sure to briefly introduce your background, and explain why you would like to work with us.
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