Machine Learning Engineer - Resource Informatics Group
Los Altos, CA
About the Job
Machine Learning Engineer
Location: Los Altos CA (Hybrid onsite 2x a week – Tuesdays & Wednesdays)
Contract: 6 months with extensions
Immigration Status: US Citizens or GC only and must be local
Interview Schedule: They will be doing one Webex and then final interview onsite
Top Must Have's:
• 4+ years of professional Client engineering experience at an AI/Client-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 Amazon EC2, S3, and/or Sagemaker.
• Experience with Bazel.
Location: Los Altos CA (Hybrid onsite 2x a week – Tuesdays & Wednesdays)
Contract: 6 months with extensions
Immigration Status: US Citizens or GC only and must be local
Interview Schedule: They will be doing one Webex and then final interview onsite
Top Must Have's:
• 4+ years of professional Client engineering experience at an AI/Client-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 Amazon EC2, S3, and/or Sagemaker.
• Experience with Bazel.
Source : Resource Informatics Group
