Software Engineer, Enterprise AI
Scale AI
Job Overview
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Job Description
Software Engineer, Enterprise AI at Scale AI
Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.
What You Will Do
- Own large new areas within our product
- Work across backend, frontend, and interacting with LLMs and ML models
- Deliver experiments at a high velocity and level of quality to engage our customers
- Work across the entire product lifecycle from conceptualization through production
- Be able, and willing, to multi-task and learn new technologies quickly
What We're Looking For
- 4+ years of full-time engineering experience, post-graduation
- Experience scaling products at hyper growth startups
- Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
- Proficient in Python or Javascript/Typescript, and SQL
- Experience with Kubernetes
- Experience with major cloud providers (AWS, Azure, GCP)
Compensation and Benefits
Compensation packages at Scale AI for eligible roles include base salary, equity, and benefits. The range displayed reflects the minimum and maximum target for new hire salaries for this position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale AI 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.
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—$270,250 USD.
About Scale AI
At Scale AI, 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.
Key skills/competency
- Software Engineering
- Enterprise AI
- Distributed Systems
- LLMs (Large Language Models)
- Machine Learning
- Scalability
- Python
- Kubernetes
- Cloud Computing (AWS, Azure, GCP)
- Full-stack Development
How to Get Hired at Scale AI
- Research Scale AI's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight extensive experience with LLMs, distributed systems, and full-stack development relevant to enterprise AI.
- Showcase problem-solving: Prepare specific examples demonstrating how you've scaled products at hyper-growth startups.
- Emphasize technical prowess: Be ready to prove proficiency in Python, JavaScript/TypeScript, SQL, Kubernetes, and major cloud providers.
- Prepare for deep dives: Expect rigorous technical interviews on system design, data structures, algorithms, and AI/ML application challenges.
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