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Jobs/Machine Learning Engineer Role/10xteam - Machine Learning Ops Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote
10xteam

10xteam - Machine Learning Ops Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote

Remote - Berlin, Brandenburg, Germany€102 - €160/hour1mo ago
RemoteEMEAArtificial IntelligenceMachine Learning EngineerAI EngineerData ScientistMLOpsLearning & DevelopmentMLflowAirflowKubeflow

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Requirements

• A senior-level MLOps engineer with significant professional experience within the EU or UK • Experienced in designing, building, and operating machine learning pipelines and infrastructure • Skilled at evaluating deployment strategies, automation, and compliance with operational standards • Comfortable working independently and providing structured, critical feedback • Available for 8–20 hours per week, with prompt availability

Responsibilities

• We are 10x.team, a platform for fractional and freelance professionals. We partner with leading AI labs to advance the capabilities of large AI systems. • Your role is both practical and high-impact. You will: • Review and refine AI-generated content related to MLOps workflows, machine learning pipelines, automation, monitoring, and deployment. • Evaluate outputs for technical validity, reproducibility, and industry best practices in MLOps. • Draft realistic scenarios covering pipeline orchestration, CI/CD for machine learning, model serving, monitoring, drift detection, and scaling infrastructure. • Assess AI reasoning in topics such as containerization, cloud platform deployment, data versioning, experiment tracking, and model lifecycle management. • Identify gaps or inaccuracies in approaches to operationalizing machine learning. • Create scenario variations from the perspective of different MLOps stakeholders: data scientists, engineers, DevOps, and business leaders. • In simple terms: you will assess and improve AI-generated content to ensure it matches real-world MLOps standards and workflows. Your work will directly enhance the quality and reliability of AI systems for MLOps tasks. • Who this is for • An MLOps engineer, ML platform developer, or machine learning operations expert • Based in the EU or UK • With several years of experience in machine learning operations, ML pipelines, or AI infrastructure • Familiar with modern MLOps tools and platforms (e.g., Kubeflow, MLflow, Sagemaker, TFX, Airflow) • Experienced in containerization, CI/CD, monitoring, and scaling ML systems • Comfortable identifying weaknesses in operational processes, tooling, or deployment strategies • Available 8 to 20 hours per week • Able to start in the coming weeks • This is a fully remote, flexible role—ideal alongside other commitments.

Benefits

• Flexible hours • Apply your MLOps expertise to real-world AI systems • Contribute to AI products used at scale • Structured onboarding and clear project scope • Potential for long-term collaboration based on performance • Screening process • Our process is straightforward and fully guided. After applying, you will complete: • A short AI-based interview • A brief written evaluation focused on MLOps reasoning and methodology • A compliance check to verify your identity and professional background • If approved, you’ll be onboarded and can start shortly after.

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