Senior Machine Learning Engineer

Industry: Recreation
Company size: 251-10K

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Job description

A well-established content-sharing platform, that is based out of the U.S. and caters to a niche audience, is looking for a Senior Machine Learning Engineer. The selected engineer will be responsible for driving critical technical roadmaps, contributing meaningfully to the team strategy, and leading day-to-day project execution to support the engineering efforts. This company is known for successfully creating a safe space for the end-users to produce, share, and engage with effectively moderated content. This company has constructively raised over $1.2bn in its series F round of funding. The selected candidate will be required to provide a 4-5 hour overlap with the PST time zone.

Job Responsibilities:

  • Develop an advanced, industrial-level ads retrieval and early ranking system for critical ML tasks
  • Study, implement, test, and bring-to-floor new model architectures, including ANN, information retrieval, recommendation system, and deep neural networks within a high dimensional information system
  • Work on product integration, large-scale data systems, and backend services 
  • Closely work with a slew of stakeholders across marketing, product, research, and engineering
  • Mentor junior engineers and become a cross-functional advocate for the team

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 5+ years of relevant experience as a Machine Learning Engineer
  • Expertise in Machine Learning- including modeling, training, evaluation, analysis, and practical work
  • Accustomed with the intricacies of ad retrievals, ranking, and data processing
  • Experience leading applied ML models using Tensorflow and Pytorch on large-scale ML systems (2+ years)
  • Previous experience (end-to-end) with training, evaluating, testing, and deploying ML models
  • Proficient with Java, Python, Golang, C++, or similar technologies
  • Expertise with statistical analysis, information retrieval, and recommendation systems
  • Prior experience orchestrating complicated data pipelines
  • Familiarity with system engineering on a large-scale dataset
  • Knowledge of the Ads domain on product and ML solutions would be a plus
  • Excellent English communication skills

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