about 4 hours ago
Base Salary
$151k - $241k/yr
Responsibilities
- Design, develop, and deploy machine learning models for real-world applications.
- Build training, evaluation, and inference pipelines for rapid experimentation.
- Analyze large datasets to improve model performance and robustness.
- Define evaluation metrics that connect model performance to product outcomes.
- Optimize models for production constraints like latency and reliability.
- Deploy machine learning systems across cloud, edge, and embedded environments.
- Monitor production model performance and improve based on field data.
- Develop MLOps capabilities including model versioning and automated testing.
- Collaborate with scientists and engineers to create scalable solutions.
- Provide technical leadership through architecture reviews and mentorship.
Requirements
- Bachelor’s or Master’s degree in a relevant field or equivalent experience.
- 8+ years of experience in developing and deploying machine learning systems.
- Strong proficiency in Python and experience with ML frameworks like PyTorch or TensorFlow.
- Experience in taking machine learning from experimentation to production.
- Familiarity with deploying models in cloud, edge, or embedded environments.
- Strong understanding of statistics and model evaluation.
- Experience with large, noisy, or multi-modal datasets.
- Familiarity with MLOps practices such as CI/CD and reproducible experimentation.
- Strong software engineering fundamentals including testing and version control.
- Ability to communicate technical decisions clearly and collaborate effectively.
Benefits
- Competitive salary and 401k with employer match.
- Discretionary paid time off and paid parental leave.
- Medical, Dental, and Vision plans.
- Fitness programs and emotional wellness support.
- Learning and development programs.
- Employee Resource Groups (ERGs) and office snacks.