Machine Learning Engineer at MLCommons Association
About MLCommons Association
At MLCommons, we democratize AI through open, state-of-the art industry-standard benchmarks and data tooling to measure quality, performance, and risk. We’re a global, non-profit consortium supported by 125+ members and affiliates, including startups, leading companies, and academics. We are a fully remote organization that supports a flexible working environment; this requires mature communication, accountability, and transparent collaboration by all team members.
About AI Risk & Reliability
AI Risk & Reliability works to support and inform the global discussion around AI safety and enable responsible development and deployment of AI systems that deliver value to users. With the AILuminate benchmark, we aim to combine the best innovations from research into AI safety into a production quality benchmark that is technically rigorous, consensus-driven, relevant, informative, and most importantly – practical.
Scope of Machine Learning Engineer.
We are looking for an ML engineer to help us advance and scale our benchmarking capabilities through the design and creation of an improved platform for benchmark execution. You will work with ML scientists, software engineers, domain experts, and our partners at frontier AI companies to figure out and build the best way forward for our next generation MLOps platform.
The Machine Learning Engineer role sits within the AI Risk & Reliability Working Group and reports to the Director of Engineering. This role necessitates at least 40 hrs/wk and is fully remote with working hours that partially overlap with the Pacific time zone.
Specific responsibilities:
Required skills and qualifications for success:
Nice-to-Have skills and qualifications:
Compensation & Timeline
Application Process
To apply, please send a resume, any links to profiles you find relevant (e.g. Github, LinkedIn, personal website) and a brief cover letter talking about your qualifications for the responsibilities, as well as contact information. We may eventually ask for professional references that can attest to the quality of your work. Send to [email protected] with the subject line “Applying for Machine Learning Engineer: AIRR.”
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