11 days ago
Base Salary
$160k - $250k/yr
Responsibilities
- Design, code, train, tune, deploy, and continuously improve machine learning and neural network models for production use cases.
- Gather and refine data, analyze production results, and develop scalable, maintainable data pipelines.
- Deploy models at scale with high throughput and uptime and conduct metric-driven experiments to improve performance.
- Write secure, scalable, performant code and contribute improvements to backend systems, products, tooling, and engineering processes.
- Develop novel machine learning algorithms and lead end-to-end development of new products.
- Mentor and onboard junior machine learning engineers and collaborate cross-functionally.
- Apply OWASP Top 10 techniques, protect information assets, and report suspected security or policy violations.
Requirements
- Bachelor's degree in computer science or a related field.
- At least 5 years of experience building production-scale machine learning models.
- Expertise with 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 across distributed systems.
- Ability to make well-reasoned feature design tradeoffs and lead end-to-end product development.
- Deep knowledge in at least one machine learning focus area, such as computer vision or NLP.
- Strong commitment to code quality, automated testing, correctness, collaboration, communication, and action-oriented execution.
Benefits
- Expected base salary range of $160,000-$250,000, with potential stock options in addition to base pay.
- Opportunity to contribute directly to a rapidly growing AI startup with offices in San Francisco, Seattle, New York, and Delhi.