AI & Machine LearningDirect Ashby career site

Software Engineer, Cloud Infrastructure

Pay: $180,000 – $300,000 per year
Location: San Mateo, CA (Remote) · On-site
Job type: Full-time
Level: Senior
Experience: 4+ years
Listed: 30 days ago

Skills & highlights for this role

AWS
Kubernetes
Terraform

Also useful

ML infrastructure
GPU orchestration
cost optimization tools

Stated benefits & perks

Health
Dental
Vision
401k match
Unlimited pto

About the Role

We’re looking for an experienced Cloud Infrastructure Engineer to join our core team at DatologyAI. In this role, you will lead the design, build, and operation of highly available, secure, and scalable cloud infrastructure that powers our training, inference, and data curation pipelines. You’ll work closely with engineering, research, and product teams to define how we deploy and manage compute resources across AWS and other cloud providers. This role is a key early hire and offers an opportunity to have a deep technical and cultural impact.

What You'll Work on

Architect and maintain our multi-cloud infrastructure (primarily AWS, potentially Azure/GCP), with a focus on reliability, security, and scalability
Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi (and similar technologies)
Design and manage Kubernetes-based systems for model training, inference, and data processing workloads
Optimize our CI/CD pipelines and streamline deployment of services across environments
Build monitoring, alerting, and logging systems to ensure high system availability and observability
Collaborate with research and engineering teams to provide infrastructure support for training large-scale ML models
Ensure our infrastructure supports various deployment models (cloud, on-prem, hybrid) for enterprise use cases
Drive cost-efficiency strategies across compute and storage resources
Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency

About You

4+ years of relevant experience
You’ve led or helped build robust infrastructure systems at a startup or fast-moving engineering organization
Deep experience working with cloud providers (especially AWS), and ideally exposure to multi-cloud or hybrid-cloud setups
Strong with Kubernetes, Terraform, and containerized architectures
Confident with systems-level debugging-networking issues, memory leaks, resource bottlenecks, etc.
Comfortable writing clean, maintainable scripts in Bash, Python, or Go
You care deeply about building secure and scalable systems and take pride in reliable infrastructure
You’re collaborative, humble, and ready to own high-impact projects end-to-end

Nice to Have

Experience supporting infrastructure for ML workloads (training pipelines, inference clusters, GPU orchestration)
Built or scaled infrastructure for teams working with large-scale datasets
Exposure to cost monitoring and optimization tools in cloud environments
Background supporting compliance and security in enterprise deployments

Compensation

At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000.

Starting pay is based on job-related skills, experience, qualifications, and interview performance.

Benefits

100% covered health benefits (medical, vision, and dental).
401(k) plan with a generous 4% company match.
Unlimited PTO policy
Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
Annual $2,000 wellness stipend.
Annual $1,000 learning and development stipend.
Daily lunches and snacks are provided in our office!
Relocation assistance for employees moving to the Bay Area.

About the Company

Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.

At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models.

Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment.

For more details, check out our recent research on synthetic data scaling (BeyondWeb) and pretraining with domain-specific data (The Finetuner’s Fallacy).

We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models.

Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.

This role is based in San Mateo, CA. We are in office 4 days a week.

Read the original posting

From DatologyAI's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.

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Common questions

What is the salary for the Software Engineer, Cloud Infrastructure role at DatologyAI?

The Software Engineer, Cloud Infrastructure posting at DatologyAI states compensation of $180,000 – $300,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on DatologyAI's official career site.

Where is the Software Engineer, Cloud Infrastructure job at DatologyAI located?

Yes, this Software Engineer, Cloud Infrastructure opening at DatologyAI is listed as San Mateo, CA (Remote) (On-site). Always check DatologyAI's application page for specific state eligibility or relocation policies.

What qualifications are required for Software Engineer, Cloud Infrastructure at DatologyAI?

For the Software Engineer, Cloud Infrastructure role, DatologyAI highlights 4+ years of relevant experience; experience with AWS, Kubernetes, Terraform. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.

How do I apply for the Software Engineer, Cloud Infrastructure position at DatologyAI?

This listing links directly to DatologyAI's Ashby application page. You can apply directly on DatologyAI's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.

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