Software Engineer, Cloud Efficiency

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that's enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. In this role, you will help design and develop the foundational platforms and systems that power our cloud infrastructure, with a strong focus on cloud efficiency, cost optimization, and hosting cost attribution. This position offers wide exposure to the forefront of AI infrastructure and large-scale system design, as seen across enterprises, startups, governments, and large tech companies.

You will:

• Design, implement, and optimize core platform services with a focus on reducing cloud spend and improving resource utilization across compute, storage, and network layers.
• Collaborate closely with stakeholders and internal customers to define requirements and architect scalable, cost-efficient solutions in AWS and other public cloud environments.
• Analyze system performance and usage trends to identify opportunities for cost savings through right-sizing, autoscaling, reserved instance strategies, and architectural improvements.
• Partner with product engineering and infrastructure teams to improve orchestration, observability, and automation for efficient deployment and operation of distributed systems.
• Present insights, metrics, and recommendations on cloud usage and efficiency to engineering and business stakeholders.
• Proactively drive process enhancements and introduce new tools or frameworks that improve the balance between system performance, reliability, and cost.

Ideally you'd have:

• 3+ years of full-time engineering experience with a focus on back-end and cloud infrastructure systems.
• Deep understanding of distributed systems, cloud cost models, and AWS services (EC2, ECS/EKS, S3, Lambda, RDS, GPU instances, etc.).
• Demonstrated experience optimizing large-scale cloud deployments for performance and cost, including autoscaling, spot instance usage, and workload scheduling.
• Proven track record of independent ownership of engineering projects that delivered measurable efficiency or cost improvements.
• Excellent communication skills with the ability to explain technical trade-offs and cost implications to both engineering and non-technical audiences.
• Proficiency with containerization and deployment technologies such as Kubernetes, Terraform, and Docker.
• Familiarity with orchestration tools like Temporal or AWS Step Functions, and with both NoSQL (MongoDB) and SQL (Postgres) databases.
• Solid grasp of software engineering best practices, CI/CD (CircleCI), and infrastructure-as-code principles.

Nice to haves:

• Experience with cloud cost management platforms (e.g., CloudHealth, Kubecost, AWS Cost Explorer).
• Experience with GCP/Azure is a plus (although deep AWS experience is required).
• Familiarity with FinOps principles and cross-team cost governance.
• Experience working with data warehouse or ETL tools (Snowflake, dbt, Dagster) to implement customized data reporting streams.
• Experience with LLM tools/platforms and API key management (i.e., LiteLLM)
• Experience scaling systems efficiently in high-growth startup environments.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,200—$270,300 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision. 

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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