Applied Machine Learning Engineer
Inference
About this role
An Applied Machine Learning Engineer at Inference.net is responsible for building and enhancing the core ML systems for a custom model training platform, overseeing the entire training lifecycle from data intake to model delivery. The role involves creating and maintaining data processing pipelines, developing evaluation frameworks, and applying advanced ML techniques to ensure model quality at scale. This position requires a strong background in AI model training, particularly with PyTorch and transformer architectures, and includes collaboration with infrastructure teams to optimize training workflows on a GPU fleet.
Skills
About Inference
inference.netInference.net is an innovative platform that specializes in AI inference solutions, enabling businesses to effectively train and host custom large language models tailored to their specific needs. The company offers a range of services, including serverless API and batch inference capabilities, designed to deliver improved performance and cost-efficiency compared to traditional models. With a focus on reducing latency and enhancing model accuracy, Inference.net empowers organizations to leverage AI technologies across various modalities such as text, image, and video. Their mission is to provide high-quality, reliable AI solutions that optimize deployment processes and drive operational excellence for their clients.
About Inference
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Leadership Team
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
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Salary
$220k – $320k
per year