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
Partner with other engineers to translate complex inference requirements into technical solutions
Make critical architectural decisions balancing performance with system reliability
Lead technical discussions and mentor junior engineers on infrastructure best practices
Contribute to long-term technical strategy and infrastructure roadmap

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.
Advanced understanding of distributed systems concepts and performance tuning
Proven experience designing observability systems
Track record of leading technical initiatives and mentoring engineers
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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

GoPythonKubernetesGPU capacity managementinfrastructure automationobservability systemsdistributed systemsperformance tuningML/AI workloadsMLOps

Soft Skills

leadershipmentoringtechnical discussionscollaborationarchitectural decision-making

Certifications

Bachelor's degree in Computer Science