Staff Cloud Platform Engineer
Senior / Staff Cloud Platform Engineer (ML Platform)
Location: South San Francisco, CA (4 Days Onsite)
Compensation: $220,000 - $290,000 Base + Bonus
About the Role
We're seeking a Senior or Staff Cloud Platform Engineer to help build and scale the cloud infrastructure powering advanced machine learning and research workloads. This role sits at the intersection of platform engineering, cloud infrastructure, Kubernetes, and developer tooling, with a strong focus on enabling researchers and engineers to move faster through automation and platform development.
This is a highly hands-on engineering role, and strong Python development expertise is a non-negotiable requirement. The ideal candidate has extensive experience building production-grade infrastructure, platform services, automation frameworks, and operational tooling using Python.
What You'll Do
- Architect and operate large-scale cloud infrastructure within GCP.
- Build and maintain platform services, automation tooling, and infrastructure applications using Python.
- Develop internal developer platforms and self-service tools that improve engineering productivity.
- Design and manage Kubernetes-based environments supporting machine learning and distributed compute workloads.
- Implement Infrastructure as Code using Terraform.
- Build automated workflows for infrastructure provisioning, governance, security, and compliance.
- Drive improvements in observability, reliability, performance, and cloud cost optimization.
- Partner closely with software engineers, ML engineers, and researchers to deliver scalable platform solutions.
- Establish best practices around platform engineering, cloud operations, and automation.
Required Qualifications
MUST HAVE
- Strong production-level Python development experience.
- Python should be a primary language, not simply a scripting tool used occasionally.
- Experience building infrastructure tooling, platform services, automation frameworks, APIs, or operational systems in Python.
- Ability to write clean, maintainable, and scalable Python code in a production environment.
Additional Requirements
- 7+ years of experience in Platform Engineering, Cloud Engineering, SRE, DevOps, Infrastructure Engineering, or related disciplines.
- Deep expertise with Google Cloud Platform (GCP).
- Strong Kubernetes administration experience in production environments.
- Experience with Terraform and Infrastructure as Code.
- Experience with Docker, CI/CD pipelines, and cloud-native technologies.
- Strong understanding of distributed systems, cloud architecture, networking, and security.
- Excellent troubleshooting and systems design skills.
Preferred Experience
- ML platform, AI infrastructure, or research computing environments.
- GPU, TPU, HPC, or distributed compute orchestration.
- Golang experience.
- Experience building internal developer platforms.
- Background working in fast-paced, highly technical environments.
- A strong intellectual curiosity for life sciences
Why This Opportunity
- Own foundational infrastructure used across the organization.
- Influence the architecture of a next-generation ML platform.
- Work on challenging cloud, Kubernetes, and distributed systems problems.
- Collaborate directly with highly technical engineering and research teams.
- Competitive compensation package with a $220K-$290K base salary plus bonus.
Location
South San Francisco, CA
4 days onsite per week
Note: Candidates without significant, hands-on Python engineering experience will not be considered. Python is a core requirement for this role.
FAQs
Congratulations, we understand that taking the time to apply is a big step. When you apply, your details go directly to the consultant who is sourcing talent. Due to demand, we may not get back to all applicants that have applied. However, we always keep your resume and details on file so when we see similar roles or see skillsets that drive growth in organizations, we will always reach out to discuss opportunities.
Yes. Even if this role isn’t a perfect match, applying allows us to understand your expertise and ambitions, ensuring you're on our radar for the right opportunity when it arises.
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That's why we recommend registering your resume so you can be considered for roles that have yet to be created.
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