Senior Staff Software Engineer, Cloud AI Infrastructure

5 days ago

Remote, United StatesStaff+

Base Salary

$214k - $267k/yr

Responsibilities

Lead and mentor a team of cloud software engineers while providing technical and career guidance.
Define and execute the cloud technical roadmap aligned with business and product goals.
Architect, implement, and operate scalable, secure, high-availability GCP systems for ML workloads and large-scale data ingestion.
Design and build ML pipelines processing hundreds of thousands of images daily for model iteration and deployment.
Optimize GPU resource management, model-serving throughput, latency, autoscaling, and cost efficiency.
Build canary and staging environments supporting progressive deployments and system resilience.
Collaborate with ML, DevOps, data science, and robotics teams on APIs, data models, and cloud-robot workflows.
Implement repeatable Infrastructure-as-Code deployments using Pulumi, Terraform, or equivalent tools.
Establish cloud observability systems and promote coding, design, distributed-systems, and cloud-ML best practices.

Bachelor’s or master’s degree in computer science, software engineering, or a related field.
10+ years of professional software engineering experience, including 3+ years in cloud architecture or large-scale distributed systems.
Proven experience designing and operating GCP-based machine-learning systems at scale.
Expertise with GCP services including GKE, Dataflow, BigQuery, Cloud Run, Pub/Sub, Vertex AI, and Cloud Storage.
Strong proficiency in Go, Python, or TypeScript.
Experience with ML pipelines, GPU workload optimization, autoscaling, resource scheduling, high-availability systems, and fault-tolerant distributed systems.
Hands-on experience with Docker and Kubernetes, plus Pulumi or Terraform and CI/CD systems such as Jenkins or GitHub Actions.
Understanding of cloud security, networking, observability, and secure cloud practices.
Preferred experience includes robotics data pipelines, fleet management, IoT-scale ingestion, self-hosted ML inference, Vertex AI, Kubeflow, TensorFlow Serving, event-driven architectures, Kafka, and SOC2/ISO27001-compliant systems.
Strong problem-solving, communication, leadership, and technical mentorship skills.

Remote anywhere in the United States or hybrid in San Diego, with relocation available.
Discretionary annual target bonus and stock options.
401(k) plan with match, no waiting period, and immediate vesting.
Medical, dental, vision, life, disability, HSA, EAP, legal/identity support, and pet insurance benefits.
Medical and dependent-care Flexible Spending Accounts.
Flexible vacation, paid sick leave, volunteer time off, 10 paid company holidays, and a winter company shutdown.
San Diego office perks include daily on-site lunch, an on-campus gym with pool and tennis courts, and colleague events.
Internal continuous learning events and opportunities to share personal interests and hobbies.