11 days ago
San Francisco, CA, USAEntry Level / Mid Level
Base Salary
$120k - $180k/yr
Responsibilities
- Design, code, train, tune, deploy, monitor, and improve neural network models for production use cases.
- Gather and refine data and analyze real-world model performance to improve accuracy and speed.
- Build scalable, maintainable data pipelines for large datasets, including datasets with millions of files.
- Deploy machine learning models at scale with high throughput and uptime.
- Collaborate closely with Backend, DevOps, and internal data-labeling teams.
- Apply OWASP Top 10 techniques and follow information-asset protection policies.
- Report suspected security or policy violations and breaches to the appropriate authority.
Requirements
- Bachelor’s or graduate degree in computer science or a similar technical field, with significant mathematics or statistics coursework.
- 1–2 years of industry machine learning experience.
- Experience training and deploying a deep learning model for image, NLP, video, or audio applications, either professionally or as a personal project.
- Strong experience with a high-level machine learning framework such as TensorFlow, Caffe, or Torch, plus familiarity with the others.
- Strong Python skills, particularly for machine learning frameworks.
- Ability to prototype data pipelines using Python, Node.js, Bash, and Linux command-line tools for large datasets.
- Working knowledge of C++, Scala, Spark, SQL, Cassandra, and Docker.
- Knowledge of current deep neural network research, architectures, theory, motivations, and implementation techniques.
- Strong communication and collaboration skills.