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HiveBrand

Posted 53 months ago

Open

Machine Learning Manager

San FranciscoOn-siteFull-time

AI Summary

Machine Learning Manager leads ML engineers, mentors the team, and drives end-to-end model development from data collection to deployment at scale.

About this role

About Hive

Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!

Machine Learning Manager

In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential. We value hard workers who have no qualms working with terabyte-scale datasets. We’re interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.

Responsibilities

  • Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
  • Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
  • Participate in products technical design and architecture
  • Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
  • Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
  • Implement and manage security protocols such as training, code review, and best practices
  • Own and manage the risk and security of your business function in coordination with the Security Team
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority

    • Requirements

  • Undergraduate or graduate degree in computer science or similar technical field
  • 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
  • Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
  • 2+ years experience managing machine learning teams
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
  • Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
  • Have experience collaborating with product managers and labeling team in delivering model improvements

    • Skills

    Audio ProcessingCode ReviewComputer VisionData CollectionData LabelingData PrivacyDeep LearningDeploymentDevOps CollaborationExperimentationModel EvaluationModel TrainingNatural Language ProcessingProduct CollaborationProduction DeploymentRisk ManagementRoadmap PlanningSecurity Best PracticesTeam LeadershipTestingTraining

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