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Staff Machine Learning Engineer

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Staff Machine Learning Engineer in USA new

  • Scale AI
  • Full time
  • Email
  • Washington, DC

Responsibilities

  • Lead the architecture and implementation of agentic AI systems for long-horizon reasoning, orchestration, and system-level reliability.
  • Build agents for geospatial reasoning over maps and spatial data.
  • Design retrieval systems for large collections of static and semi-structured documents.
  • Fine-tune and evaluate embedding models for mission-critical datasets.
  • Design memory systems for persistent state, long contexts, and learning from prior interactions.
  • Own shared agentic infrastructure and core libraries across teams, products, and Public Sector contracts.
  • Define evaluation strategies including robustness testing, failure-mode analysis, and production regression testing.
  • Partner with engineering managers, product leaders, and researchers to scope initiatives and unblock execution.
  • Mentor engineers and raise standards for system design, ML rigor, and production readiness.
  • Travel approximately 10% for customer interactions and team needs.

Requirements

  • 8+ years of experience building and deploying applied ML systems in production environments.
  • Deep experience with agentic systems, autonomous workflows, or multi-step reasoning and acting ML systems.
  • Strong ML systems engineering background, including model serving, pipelines, monitoring, and evaluation.
  • Hands-on experience with retrieval systems, embeddings, or representation learning.
  • Proficiency in Python and modern ML frameworks such as PyTorch, with end-to-end system design ability.
  • Staff-level experience setting technical direction, owning ambiguous problems, and driving initiatives from 0 to 1 into production.
  • Experience balancing performance, cost, reliability, and development velocity.
  • Active TS security clearance.
  • Preferred experience with air-gapped, classified, disconnected, on-premises, or customer data-center deployments.
  • Preferred experience with DoD, intelligence community, or federal mission users.
  • Preferred hands-on experience with geospatial data or GEOINT.
  • Preferred experience with embedding-model training or fine-tuning, instruction tuning, LoRA/PEFT, or RLHF.
  • Preferred experience building evaluation infrastructure for non-deterministic systems, including LLM-as-judge, agent regression suites, or production drift detection.
  • Preferred experience turning forward-deployed prototypes into supported and documented capabilities.

Benefits

  • Base salary, equity eligibility, and comprehensive health, dental, and vision coverage are provided for eligible roles.
  • Retirement benefits, a learning and development stipend, and generous paid time off are offered.
  • The role may be eligible for a commuter stipend.
  • The position is full-time in Washington, DC, with approximately 10% travel.
  • Candidates must wait 90 days before reconsideration for the same role.

Salary: $274k - $343k/yr

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....

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