MLOps Engineer – ML Platform Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇲🇽 Mexico – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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VALCE Talent Solutions

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🤝 B2B

🎯 Recruiter

💼 Consulting

B2B • Recruitment • Consulting

VALCE Talent Solutions is a company specializing in nearshoring, IT talent acquisition, and consultancy aimed at helping businesses expand globally, particularly in Mexico, LATAM, and the United States. They offer customized solutions that include talent recruitment, workforce management, and the integration of technology and artificial intelligence to enhance business processes. With a strong focus on strategic consulting, VALCE aims to connect technology, talent, and tangible results, boasting a robust network of IT professionals and a proven track record of successful placements and project scaling.

📋 Description

• Monitor AI models and agents in production for performance, latency, errors, and availability • Track model drift, data distribution changes, and output stability • Observe business KPIs linked to AI behaviour • Detect and triage production incidents related to AI behaviour or degradation • Execute rollbacks, throttling, or model disabling when thresholds are breached • Support root-cause analysis and post-incident reviews • Support deployment, versioning, and release of AI models and agents using CI/CD-style pipelines • Maintain registries and metadata covering model ownership, lineage, risk classification, and approvals • Support safe promotion of models and agents through dev, test, and production environments • Ensure AI systems adhere to Responsible AI principles, internal controls, and audit requirements • Maintain audit trails, logs, and approval artefacts for risk, compliance, and regulators • Support fairness, bias, explainability, and transparency monitoring in production • Integrate AI systems with monitoring, logging, and alerting platforms • Work with cloud infrastructure, including containers, event streaming, and APIs • Collaborate with product, engineering, and data teams to standardise AI Ops patterns and blueprints

🎯 Requirements

• Strong Python skills and experience supporting ML or LLM-based systems • Understanding of Model Ops / MLOps, especially the operational phase after deployment • Experience with monitoring and logging systems • Experience with CI/CD pipelines • Experience with containerised deployments, e.g. Docker-based runtimes • Familiarity with cloud platforms, Azure preferred • Experience with production troubleshooting • Ability to work cross-functionally with product, data science, engineering, and risk teams