Dice
Machine Learning Engineer
Dice, Los Altos, California, United States, 94024
Role:
Machine Learning EngineerLocation:
Los Altos CA (Hybrid onsite 2x a week)Duration:
ContractThey will be doing one Webex and then final interview onsiteTop Must Haves:
4+ years of professional ML engineering experience at an AI/ML-focused organization.Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision.Experience training large-scale foundation models (VLMs, text-to-video models, etc) utilizing distributed training and high-performance optimization techniques such as quantization, mixed precision, model parallelism, data parallelism or FSDP.Strong proficiency in Python and software development best practices such as unit testing, documentation, code review, continuous integration, and dependency management.Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management.An ability to move fast and switch between modes of rapid prototyping and robust implementation as required.Nice to Haves:
Experience deploying models on embodied systems/robots.Experience working in mixed teams of research scientists and engineers.Experience with Amazon EC2, S3, and/or Sagemaker.Experience with Bazel.
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Machine Learning EngineerLocation:
Los Altos CA (Hybrid onsite 2x a week)Duration:
ContractThey will be doing one Webex and then final interview onsiteTop Must Haves:
4+ years of professional ML engineering experience at an AI/ML-focused organization.Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision.Experience training large-scale foundation models (VLMs, text-to-video models, etc) utilizing distributed training and high-performance optimization techniques such as quantization, mixed precision, model parallelism, data parallelism or FSDP.Strong proficiency in Python and software development best practices such as unit testing, documentation, code review, continuous integration, and dependency management.Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management.An ability to move fast and switch between modes of rapid prototyping and robust implementation as required.Nice to Haves:
Experience deploying models on embodied systems/robots.Experience working in mixed teams of research scientists and engineers.Experience with Amazon EC2, S3, and/or Sagemaker.Experience with Bazel.
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