over 4 years ago
Base Salary
$160k - $250k/yr
Responsibilities
- Design, implement, train, tune, deploy, and continuously improve neural network models for production use cases.
- Gather and refine data, analyze production results, and build scalable data pipelines.
- Write and maintain scalable, performant, secure, cross-platform code.
- Contribute improvements to product and core backend systems, engineering standards, tooling, and processes.
- Develop novel machine learning algorithms and conduct metric-driven research experiments.
- Mentor and help onboard junior machine learning engineers.
- Apply OWASP Top 10 techniques and follow information-security policies and reporting procedures.
Requirements
- Bachelor's degree in computer science or a related field.
- At least five years of experience building production-scale machine learning models.
- Knowledge of modern machine learning frameworks such as PyTorch or TensorFlow.
- Expertise in Python and/or shell scripting, particularly for data analysis.
- Experience writing code and training models across distributed systems.
- Ability to make well-reasoned feature-design tradeoffs and lead end-to-end development of new products.
- Deep knowledge in at least one machine learning focus area, such as computer vision or natural language processing.
- Commitment to high code quality, automated testing, engineering best practices, correctness, collaboration, and communication.
Benefits
- Opportunity to work at a rapidly growing AI startup with direct impact on the company’s development.
- Stock options may be offered in addition to base compensation.
- The company has offices in San Francisco, Seattle, and Delhi.