Base Salary
$288k - $360k/yr
Responsibilities
- Partner with enterprise customers to understand their infrastructure, data pipelines, and business requirements.
- Design and implement integrations between Scale AI’s platform and customer cloud platforms, data warehouses, and internal APIs.
- Build data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows.
- Deploy and configure AI models and agents within customer security and compliance boundaries.
- Develop production-grade AI agents and architect multi-agent systems for customer use cases.
- Build evaluation frameworks, prompt libraries, human-in-the-loop workflows, and feedback mechanisms to improve AI performance.
- Implement RAG systems and fine-tuning pipelines where appropriate.
- Serve as the primary technical contact for strategic enterprise accounts and provide customer training and knowledge transfer.
- Collaborate with customer data scientists, ML engineers, and software developers, as well as Scale product and engineering teams.
- Document technical architectures, integration patterns, and best practices.
- Debug issues across data pipelines, infrastructure, and model outputs; rapidly prototype solutions and identify opportunities for productization.
Requirements
- 12+ years of software engineering experience with strong foundations in data structures, algorithms, and system design.
- Production Python expertise and experience with modern ML/AI frameworks such as LangChain, LlamaIndex, Hugging Face, or the OpenAI API.
- Experience with AWS, GCP, or Azure and modern data infrastructure.
- Ability to navigate ambiguous requirements, solve complex problems, and rapidly iterate toward solutions.
- Excellent communication skills for explaining complex technical concepts to technical and non-technical audiences.
- Deep understanding of LLMs, prompting techniques, embeddings, and RAG architectures is preferred.
- Production experience building and deploying AI agents or autonomous systems is preferred.
- Knowledge of vector databases and semantic search systems is preferred.
- Open-source AI/ML contributions are preferred.
- Experience with Docker, Kubernetes, CI/CD pipelines, Terraform, Bicep, or other infrastructure-as-code tools is preferred.
- Familiarity with enterprise security, compliance, and governance requirements such as SOC 2, GDPR, or HIPAA is preferred.
- Technical consulting, solutions engineering, product engineering, technical enablement, or teaching experience is preferred.
Benefits
- Comprehensive health, dental, and vision coverage.
- Retirement benefits, learning and development stipend, generous PTO, and potentially a commuter stipend.
- Full-time role located in San Francisco, New York, or Seattle, with the specific location referenced in the posting subtitle.
- Eligible roles may include equity-based compensation.
Categories
About Scale AI
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. We 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. The Scale Generative AI Platform allows customers to build, evaluate, and control advanced AI agents and applications that continuously improve. The Scale Data Engine provides the technology to collect, curate, and annotate high-quality datasets. Through our Scale Labs, we test models with rigorous benchmarks and novel research to ensure breakthroughs translate into systems people can trust. Scale powers the most advanced LLMs and generative models in the world through RLHF, data generation and model evaluation. We work 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.