over 4 years ago
Base Salary
$160k - $250k/yr
Responsibilities
- Design, code, train, tune, deploy, and monitor neural network models for production use cases.
- Gather and refine data and plan scalable, maintainable data pipelines.
- Deploy models at scale with high throughput and uptime while continuously improving accuracy and speed.
- Write scalable, performant, secure, and shareable code.
- Contribute improvements to product and core backend systems, engineering standards, tooling, processes, and security.
- Develop novel ML algorithms and conduct metric-driven experiments to improve model performance.
- Mentor and help onboard junior machine learning engineers.
- Collaborate cross-functionally and apply OWASP Top 10 techniques to protect code from vulnerabilities.
- Follow information-asset protection policies and report suspected security or policy violations.
Requirements
- Bachelor’s degree in computer science or a related field.
- At least five 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 models across distributed systems.
- Knowledge of at least one machine learning focus area, such as computer vision or natural language processing.
- Ability to lead end-to-end development of new products and make well-reasoned feature tradeoffs.
- Strong commitment to code quality, automated testing, correctness, and engineering best practices.
- Strong interpersonal and communication skills, comfort with ambiguity, and a bias toward action.
Benefits
- Health, vision, and dental insurance
- Gym membership
- Paid vacation
- Equity grants may be offered
- The role is based within Hive’s San Francisco, Seattle, or Delhi office locations