MLOps Engineer – AI Trainer

🕒 March 28

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10x.Team

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

🏪 Marketplace

👥 HR Tech

💰 $1.1M Seed Round - 10x Team on 2024-05

Marketplace • HR Tech

10x. Team is a marketplace platform that connects ambitious companies with senior fractional and freelance executives and specialized professionals. The service offers flexible engagement models (consultation, fixed-scope projects, subscriptions, hourly mission posts) and tools like an AI recruiter to streamline hiring, vet talent, and manage contracting, IP and compliance. It focuses on helping startups, scaleups and corporates access C‑level and operational expertise on demand to accelerate growth and solve complex challenges.

📋 Description

• 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.

🎯 Requirements

• 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

🏖️ Benefits

• Flexible hours • Fully remote • 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