Software Engineer, Scale AI
Enterprise
2 days a week in office
Training and validation data for AI applications
Open for applications
Training and validation data for AI applications
1001+ employees
Open for applications
2 days a week in office
1001+ employees
Company mission
To develop reliable AI systems for the world's most important decisions.
Role
Who you are
- If you're excited about pushing the boundaries of AI-driven product development, we want to hear from you
- 4+ years of experience developing large-scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability
- Proficiency in Python or TypeScript, with experience designing high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS
- Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools like Terraform
- Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data-intensive applications
- Hands-on experience with GenAI applications, model integration, or AI agent systems—understanding how to deploy, evaluate, and scale AI workloads in production
- Strong understanding of observability, CI/CD, and security best practices for running services in enterprise or multi-tenant environments
- Ability to balance rapid iteration with production-grade quality, shipping reliable backend systems in fast-paced environments
- Collaborative mindset, working closely with ML, infra, and product teams to bring complex GenAI systems into production at enterprise scale
What the job involves
- We’re looking for a Backend Engineer to help bring large-scale GenAI systems to production
- In this role, you’ll build the core infrastructure that powers AI products for some of the world’s largest enterprises—designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance.
- This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale
- At Scale, we don’t just follow AI advancements — we lead them
- Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption
- Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI
- Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale’s and customers’ infrastructure
- Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production-scale AI adoption
- Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads
- Optimize backend performance for latency, throughput, and cost—ensuring AI applications can operate at enterprise scale across hybrid and multi-cloud environments
- Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments
- Collaborate with ML and product teams to bring cutting-edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks
- Continuously improve reliability and scalability, applying strong engineering practices to make AI systems robust, maintainable, and enterprise-ready
Salary benchmarks
Our take
When training AI models, lack of access to large scale, high quality, labelled data is often the barrier preventing machine learning teams from building something great. In fact, labelled data is even more essential than the algorithms themselves. Scale AI is solving this by providing easy access through developer APIs to a huge variety of labelled data sets covering a large range of areas within computer vision and natural language processing.
It seems that almost every company now is offering artificial intelligence enabled products to automate every aspect of our lives. So, by positioning themselves as the go-to source for high quality tagged data, Scale AI is in an excellent position as the AI sector continues it's exponential growth.
With innovative AI projects across a range of sectors including retail, energy, and healthcare, Scale AI is now a leader in the industry alongside OpenAI. It continues to forge partnerships with fintech tools and software engine developers such as Brex and Luminar to continue its evolution of digital markets.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 7 rounds)
May 2024
$1bn
SERIES F
Apr 2021
$325m
SERIES E
Total funding: $1.6bn
Company benefits
- Health & Wellbeing: Our holistic approach to supporting Scaliens includes comprehensive health coverage, dental and vision insurance, mental healthcare services, and more. PTO policies and accommodating schedules ensure you’ll get time off when you need it to relax and recharge. Note that our offerings may vary by region as we strive to respond to the unique needs of Scaliens around the globe.
- Personal & Career Growth: Continuously learn and grow through annual learning & development stipend, attending leadership breakfasts, manager training, speaker series, and joining an ERG.
- Building Scale Community: We welcome guests to our offices, and you can expect to see Scalien families and friends around. Join local happy hours, and accept invites to game nights, book clubs, and many other employee-led community events.
- Parental Support: Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life.
Company HQ
Rincon Hill, San Francisco, CA
Leadership
Alexandr Wang
(Founder & CEO)Previously, Alexandr was an Algorithm Developer at Hudson River Trading, a Tech Lead and Quora and a Software Engineer at Addepar.
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