Senior Software Engineer, Platform

Scale AI; San Francisco, New York (CA, NY); On-site; USD 140,000 - 200,000; Full time

Job summary

Scale AI in San Francisco is seeking a Platform Engineer to design and build foundational data platforms, architect Scale’s core cloud infrastructure, and streamline how engineers develop, test, and deploy software. You will collaborate with cross-functional teams to define and deliver new features, improve existing tooling, and promote best practices across the engineering organization.

The ideal candidate has 3+ years of backend engineering experience, deep knowledge of distributed systems,

Qualifications

• 3+ years of full-time backend engineering experience.
• Strong understanding of distributed systems and cloud platforms.
• Experience with containerization and modern deployment tooling.
• Ability to own projects from design to deployment and communicate with stakeholders.

Responsibilities

• Design and implement foundational platforms and data infrastructure.
• Collaborate with cross-functional teams to define features.
• Drive improvements to development processes and tooling.
• Present technical information to stakeholders and provide guidance.

Skills

Backend systems

Distributed systems

AWS

Kubernetes

Docker

CI/CD tooling

Tools

Kubernetes

Terraform

Docker

Temporal

AWS Step Functions

MongoDB

PostgreSQL

CircleCI

Job description

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 support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

You will:

• Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborating with cross-functional teams to define, design, and deliver new features.
• Proactively identifying opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
• Presenting technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.

Ideally you’d have:

• 3+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
• Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
• Show a track record of independent ownership of successful engineering projects.
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
• Experience with orchestration platforms, such as Temporal and AWS Step Functions.
• Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).

Nice to haves:

• Experience