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Hive

Builds AI models for content safety and search

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSeattle, WA, USAIn-person

About the Job

Requirements

  • A bachelor's degree in computer science or a related field is required.
  • At least 5 years of experience building production-scale machine learning models is required.
  • Knowledge of modern machine learning frameworks such as PyTorch or TensorFlow is required.
  • Expertise in scripting languages such as Python and/or shell scripts, particularly for data analysis, is required.
  • Experience writing code and training across distributed systems is required.
  • The ability to understand and make well-reasoned tradeoffs when designing features is required.
  • The ability to lead end-to-end development of new products is required.
  • Strong knowledge in at least one machine learning focus area, such as computer vision or natural language processing, is required.
  • A commitment to high code quality, automated testing, and other engineering best practices is required.
  • Attention to detail and a focus on correctness are required.
  • The ability to work with ambiguity and scope solutions with teammates is required.
  • Strong interpersonal and communication skills and a bias toward action are required.

Responsibilities

  • Design and code neural networks, gather and refine data, train and tune models, deploy models at scale with high throughput and uptime, and analyze their real-world results to continuously improve accuracy and speed.
  • Write and maintain scalable, performant, and secure code that can be shared across platforms.
  • Contribute to the product and core backend systems by suggesting and executing improvements.
  • Improve engineering standards, tooling, processes, and security.
  • Develop novel, accurate, and performant machine learning algorithms for use at scale.
  • Conduct metric-driven research experiments to improve model performance.
  • Provide mentorship to and help onboard junior machine learning engineers.
  • Collaborate cross-functionally with other teams.
  • Use OWASP Top 10 techniques to secure code from vulnerabilities.
  • Maintain awareness of industry best practices for data maintenance and handling as they relate to the role.
  • Adhere to policies, guidelines, and procedures pertaining to the protection of information assets.
  • Report actual or suspected security or policy violations or breaches to an appropriate authority.

About the Company

Hive

Builds AI models for content safety and search

Hive builds AI models for businesses that need to understand, search, and generate digital content, with a focus on online platforms and media companies. Its content moderation tools classify harmful material in images, video, text, and audio, while separate models identify synthetic media and impersonation. Developers connect the models to their applications through cloud APIs, and teams use dashboards to review flagged content and manage decisions. Customers pay for the amount of content processed, with custom pricing and support for enterprise deployments; the platform also runs image search and content generation models. Founded in 2013, Hive is headquartered in San Francisco.

Company size
201-500
Company stage
Series A
Total funding
$20.9M
Headquarters
San Francisco, CA
Founded
2013

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