over 5 years ago
San Francisco, CA, USAEntry Level / Mid Level
Base Salary
$120k - $180k/yr
Responsibilities
- Design and code neural networks for production machine learning use cases.
- Gather, refine, train, and tune models using large-scale datasets.
- Deploy models at scale with high throughput and uptime.
- Analyze production results and continuously improve model accuracy and speed.
- Plan and build scalable, maintainable data pipelines.
- Collaborate with Backend, DevOps, and internal data labeling teams.
- Apply OWASP Top 10 techniques to secure code from vulnerabilities.
- Follow information asset protection policies and report suspected security or policy violations.
Requirements
- Undergraduate 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.
- Successful experience training and deploying a deep learning model for image, NLP, video, or audio, either professionally or as a personal project.
- Strong experience with TensorFlow, Caffe, or Torch and familiarity with the other frameworks.
- Strong Python skills applied to machine learning frameworks.
- Ability to prototype data pipelines using Python, Node, Bash, and Linux command-line tools for large datasets.
- Working knowledge of C++, Scala/Spark, SQL, Cassandra, and Docker.
- Current understanding of deep neural network research, architectures, theory, motivations, and implementation.
- Strong communication and collaboration skills.
Benefits
- Opportunity to work on deep learning technology and proprietary AI models at a growing AI startup
- Direct impact on company development and exposure to the full machine learning stack
- Base salary of $120,000-$180,000, with possible stock options
- Work location information is not stated
Categories
Data EngineeringML Engineering