10xteam - Machine Learning Operations Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote
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, project-based freelance work—100% remote • Use your machine learning operations expertise to help build better AI • Make a direct impact by shaping the AI’s understanding of complex ML workflows and deployment challenges • Free access to our AI Academy for professional upskilling • Structured onboarding, clear project briefs, and ongoing collaborative opportunities • After applying, you’ll receive an email detailing the steps to: • Complete a short written assessment • Participate in an AI-powered interview • Important: Your application is only complete once you finish all steps via the email link. • Please note: these AI Lab missions are not traditional job openings with fixed start dates. Project demand is highly dynamic and matching depends on your expertise, availability, and current AI Lab needs. Some experts are matched within days, while others may wait longer for a suitable project. • Help shape the next generation of AI-driven machine learning operations—apply today! • ---------------------------------------- • At 10x, there are two types of opportunities: • 1. Traditional freelance missions • These are regular project-based opportunities where the listed mission is the actual project you may work on. • 2. AI Lab roles • For AI Lab roles, we scout, review, and approve profiles for access to future project opportunities. • The missions listed for AI Lab roles are not traditional job openings. AI Lab work is often highly confidential as this exposes information of what an AI Lab is working on, and project requests are unpredictable. When an AI Lab request comes in, we often need to respond within 24 hours with suitable talent. • Matching depends on the specific needs of each AI Lab project and your niche expertise. Once your profile is reviewed and approved, you may be matched to relevant AI Lab projects when suitable opportunities arise. • This can happen within hours, but it may also take months, depending on the researchers at the AI labs and their project needs.
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT