# Senior/Staff Machine Learning Engineer, General Agents, Enterprise GenAI

**Company**: Scale AI
**Location**: San Francisco, CA; New York, NY
**Work arrangement**: hybrid
**Experience**: senior|staff
**Job type**: full-time
**Salary**: $264,800-$331,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q112629176

**Apply**: https://job-boards.greenhouse.io/scaleai/jobs/4658162005
**Canonical**: https://yubhub.co/jobs/job_9c235fca-4e3

## Description

As a Senior/Staff Machine Learning Engineer on the General Agents team, you'll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems.

You will work across the full agent lifecycle,from model and system design to evaluation, deployment, and iteration,bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

Key responsibilities include:

- Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.

- Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.

- Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.

- Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.

- Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.

- Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.

- Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideal candidates will have:

- 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.

- Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.

- Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.

- Proven proficiency in Python, including writing production-quality, testable, and maintainable code.

- Experience building systems that integrate models with external tools, APIs, databases, and services.

- Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.

- Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves include hands-on experience building AI agents using modern generative AI stacks, experience with agent frameworks, orchestration layers, or workflow systems, familiarity with evaluation, monitoring, and observability for LLM-powered systems in production, and experience deploying ML systems in cloud environments and operating them at scale.

## Skills

### Required
- Machine Learning
- Artificial Intelligence
- Python
- LLMs
- Agentic System Design

### Nice to have
- Generative AI Stacks
- Agent Frameworks
- Orchestration Layers
- Workflow Systems
- Evaluation, Monitoring, and Observability