9 months ago
Base Salary
$221k - $260k/yr
Responsibilities
- Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training.
- Develop, optimize, and maintain ML model serving infrastructure for high performance and low latency.
- Collaborate with ML and product teams to scale backend infrastructure for AI-driven products.
- Optimize compute-heavy workflows and enhance GPU utilization for ML workloads.
- Build a robust model API orchestration system.
- Define and implement strategies for scaling infrastructure as the company grows.
Requirements
- Strong experience in building and deploying machine learning models in production environments.
- Deep understanding of container orchestration and distributed systems architecture.
- Expertise in Kubernetes administration, including custom resource definitions and cluster management.
- Experience developing APIs and managing distributed systems for batch and real-time workloads.
- Excellent communication skills to interface between research and product engineering.
Benefits
- 14 paid holidays and flexible PTO for salaried employees.
- Comprehensive health plans including medical, dental, and vision coverage.
- Generous HSA contributions for those on a High Deductible Health Plan.
- Paid parental leave and family forming benefits.
- 401(k) matching to help invest in your future.
- Personal device allowance and access to pre-tax benefits.
- Monthly contributions for fitness and professional development.
- Dedicated mental health support and paid sabbatical leave after 5 years.