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Machine Learning Engineer

  • Job type: Permanent
  • Location: Sunnyvale, California
  • Salary: US$150000 - US$185000 per annum
  • Job reference: 303903/001_1528762908
  • Sector: BI & Big Data, Glocomms
  • Date posted: 12/06/2018

A cutting edge AI/ML organization that provides enterprise solutions for Fortune 2000 companies is looking for a Head Machine Learning Engineer to help the business tackle unique challenges to collaborate with operations and Data Science, and analytic environments. Since their establishment in 2014, the rapid growing start-up has found success in building a platform for one main purpose - to scale. As part of their growth story, the organization plans to expand in the market in order to increase optimization, enhance production and make a larger presence in the cloud.

JOB DESCRIPTION:

  • The Machine Learning Engineer will focus on implementing ML algorithms and solutions in partnership with the research team. This individual will spearhead the core development for implementation of mathematical functions in order to transform and mold big data to ensure a system of checks in balance. The engineer will also engage with customers and internal partners in order to provide on demand and strategic solutions based on the enterprise business' requirements.

REQUIREMENTS:

  • MS in Computer Science, Mathematics or Statistics with a major in Machine Learning or Deep Learning.

  • Technical knowledge in one or more of the following areas: Machine Learning algorithms, Statistical Modeling, Data

  • Demonstrated success in Mining, Pattern Recognition, Natural Language Processing and Deep Learning.

  • Hands-on experience doing code development in Python, Scala or JAVA including core mathematical functions, feature engineering, data manipulation functions, model analysis and library/package management.

  • Hands-on experience implementing machine learning techniques including data ingest, cleaning, and modeling.

PREFERRED:

  • Hands on experience with Spark (MLLib), TensorFlow, PyTorch, Theano, Caffe, Scikit-learn or similar products in building, testing and evaluating accuracy and performance using publicly available datasets. Contributions to one or more of these open source frameworks is also highly desired.

  • Higher education degree in Computer Science, Mathematics or Statistics with a focus on Machine Learning or Deep Learning.

  • Hands on experience using Machine Learning or Deep Learning to solve commercial problems.

  • Knowledge of distributed computing and map-reduce framework and the ability to leverage them to minimize the time to insight using large data sets.