Remote Machine Learning Engineer - RitualRitual • San Francisco, CA, United States
Remote Machine Learning Engineer - Ritual
Ritual • San Francisco, CA, United States
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job_description.job_card.job_descriptionExperience as a software engineer Experience building and serving machine learning models Familiarity with Python and related ML frameworks such as PyTorch, Tensorflow, Jax, and other open-source stacks such as HuggingFace Ability to reason through machine learning system tradeoffs A high level of end-to-end ownership and self-direction Familiarity with basic machine learning system stacks e.g. TinyML, Triton, CUDA, ROCm, Exo, MLIR, Halide, etc Familiarity with DataOps, MLOps, and ML orchestration pipelines Understanding of modern ML architectures and intuition for inference performance tradeoffs Experience or interest in working on open-source ML products Interest in building tech aligned with user privacy, computational integrity, and / or censorship resistance Experience at fast-growing companies or startups Join a passionate group of engineers, researchers, and operators on a mission to build the next generation of AI infrastructure Enjoy high-quality healthcare Plan ahead with our company 401k match Work the way you work best - Remote and / or hybrid Be rewarded for your work with our competitive salary philosophy Participate in virtual and in-person events Much much more!
About Ritual
Ritual is the network for open AI infrastructure. We build groundbreaking, new architecture on a crowdsourced governance layer aimed to handle safety, funding, alignment, and model maintenance.
Join us on the journey to decentralize AI!
About the role
We are looking for a talented and motivated Machine Learning Product Engineer to join our team. In this role, you will work on a variety of projects related to applied machine learning, including working with the product team on automating Data ETL pipelines, deploying machine learning models, and shipping customer-facing products.
- Scale up model inference and running predictions at scale on cutting-edge models
- Work end to end to connect ML models to human interfaces (e.g. APIs, browsers, and applications)
- Designing and implementing large-scale data and ML pipelines through a full end-to-end product development lifecycle
- Collaborate with a cross-functional team of engineers, researchers, product managers, designers, and operations teammates to create cutting-edge products
About you
Extras
Why join us
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