POSITION:  Machine Learning Platform Engineer

JOB DUTIES: Develop and manage the Machine Learning platform to run parallel hyperparameter tuning jobs for efficient model exploration and train models on Kubernetes. Provide tools and frameworks to deploy a machine learning model as a microservice. Build abstractions and workflows to automate the manual operations regarding machine learning projects. Create impactful features to improve the platform. Remote work is permitted within the U.S. only.

HOURS: 40 hours per week, Monday through Friday

LOCATION: Mercari, Inc., 3223 Hanover Street, Suite 110, Palo Alto, CA 94304

SALARY: $180,688 - $189,800 per year

REQUIREMENTS

Main Experience: Bachelor’s degree in Computer Science, Computer Engineering, or closely related field of study and four (4) years of experience as a Machine Learning Engineer or closely related occupation.

Special Skills: Also requires three (3) years of experience in the following:

  • Creating production level, highly concurrent, multithreaded or distributed ML models for training, validation, and inference leveraging real-time systems;
  • Kubernetes-based ML training and deployment architectures using technologies such as KubeFlow, Seldon, and KServe;
  • Heterogeneous computing and GPU programming;
  • Spark, Kafka, Presto, Airflow, or similar data streaming/processing technologies;
  • Machine/deep learning frameworks such as TensorFlow, Keras, Pytorch, Caffe, MXNet, etc;
  • Building micro service-based solutions to implement large-scale data infrastructures and ML pipelines;
  • Machine learning pipelines from standardization, normalization, clustering, modeling, scoring, and validation; and
  • ETL engineering and tools.

CONTACT: Apply online at https://careers.mercari.com/search-jobs/ or email resume to Mercari, Inc., at us_jobs@mercari.com. Please reference job title on resume. Employment and background checks may be required.

#LI-DNI

Salary

$180,688 - $189,800

Yearly based

Location

US

Remote Job

Job Overview
Job Posted:
1 year ago
Job Type
Full Time

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