Live opening · Posted 3 days ago

MLOps Engineer Expert

Harbor ML · Cérons, Nouvelle-Aquitaine, France (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyHarbor ML
LocationCérons, Nouvelle-Aquitaine, France (Remote)
Work modeYes
SourceLinkedin
ListedPosted 3 days ago

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About the role

Description supplied by the original job listing.

Harbor Expert Network
MLOps Engineer Expert
$110–$160/hrpay
Required Skills
MLOpsAgent evaluationProduction MLCI/CD for models
About Harbor
Harbor connects domain experts to the development of frontier AI models. Real-world expertise is turned into training data, evaluations, and feedback loops that improve how models perform. AI labs and enterprises use Harbor to train models and build reliable agents through advanced evaluations and field capture programs. Experts contribute directly to how AI systems learn, reason, and perform across robotics, computer vision, wearable AI, industrial inspection, healthcare, and agentic systems. Harbor identifies and vets top talent through an AI recruiter, enabling high-quality contributions at scale.
Job Description
Job title: MLOps Engineer Expert
Job type: Contractor
Location: Remote
Job summary: Evaluate agentic systems and MLOps workflows for enterprise AI programs. You review tool-use traces, deployment patterns, and reliability practices frontier labs expect.
Key responsibilities
Score agent trajectories for tool selection, recovery behavior, and task completion.
Review MLOps pipelines: versioning, monitoring, rollback, and eval gates.
Identify failure modes in multi-step agent runs (looping, hallucinated tool args, data leaks).
Document best-practice gaps relative to production SRE and ML engineering standards.
Support benchmark design for long-horizon agent and RAG evaluation suites.
Required Skills And Qualifications
3+ years shipping or operating ML systems in production environments.
Hands-on experience with observability, model registries, and automated eval hooks.
Ability to read logs, traces, and infra configs and render expert judgments quickly.
Clear written technical communication for mixed research and platform audiences.
Preferred Qualifications
Experience evaluating LLM agents, LangGraph-style workflows, or RLHF pipelines.
Contributions to open-source MLOps or agent frameworks.
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