Related skills
aws python kubernetes gcp go📋 Description
- Design and architect scalable infrastructure systems for our ML inference platform
- Lead optimization of Kubernetes deployments for efficient, cost-effective model serving
- Drive enhancements to our inference orchestration layer for complex model deployments
- Define monitoring strategies for model performance, latency, and resource utilization
- Develop advanced solutions for GPU capacity management and throughput optimization
- Establish infrastructure automation standards to streamline ML deployment workflows
🎯 Requirements
- Bachelor's degree or higher in Computer Science or related field
- 5+ years experience building production infrastructure systems
- Expert-level proficiency in Go, with Python experience a plus
- Deep expertise with Kubernetes in production environments
- Extensive experience with major cloud providers (AWS, GCP) and neo-cloud providers (Crusoe, DigitalOcean, Nebius) a plus.
- Experience with ML/AI workloads and MLOps platforms highly valued
🎁 Benefits
- Competitive compensation, including meaningful equity.
- 100% coverage of medical, dental, and vision insurance for employee and dependents
- Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
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