MLOps Platform Manager, Palantir

MLOps Platform Manager, Palantir Fully Remote | 6 Month Contract | Outside IR35 | £550 to £650 per day Overview A leading organisation is looking for an MLOps Platform Manager to take ownership of its Palantir and production ML platform environment, covering Foundry, AIP and wider MLOps services. The role will focus on ensuring the platform is reliable, secure, well-governed and scalable, while helping data science and engineering teams move models and data products into production in a structured and repeatable way. The Role This is a delivery-focused platform ownership role, sitting across: Palantir platform operations MLOps enablement Service management Security, governance and compliance Supplier and vendor management You will be responsible for the day-to-day running and improvement of Palantir Foundry, AIP and related MLOps capabilities. The role requires someone who can combine technical platform understanding with operational discipline, stakeholder management and a strong service-owner mindset. Key Responsibilities Platform Operations Own the day-to-day operation of Palantir Foundry, AIP and MLOps services Ensure strong platform availability, performance, stability and user experience Manage incidents, problems, changes, requests and escalation processes Manage platform releases, upgrades and vendor changes Maintain runbooks, support playbooks and platform documentation MLOps & Model Lifecycle Build and improve standard MLOps patterns across training, validation, deployment and monitoring Support data science and engineering teams in operationalising models end-to-end Improve CI/CD, environment management and automated testing for ML workloads Implement model monitoring across drift, performance, data quality and latency Support model lifecycle governance, including versioning, approvals, traceability and reproducibility Security, Risk & Compliance Manage platform access, authentication, authorisation and segregation of duties Work with InfoSec, compliance and governance teams to evidence controls for data and AI services Support audits across platform operations, change history, access reviews and model lifecycle controls Maintain platform controls across logging, retention, encryption and privacy Roadmap, Cost & Vendor Management Own the platform roadmap and improvement backlog Prioritise improvements based on business value, risk, cost and developer experience Manage capacity, usage monitoring and cost optimisation Manage relationships with Palantir, delivery partners and other platform suppliers Define standards, reference architectures and reusable patterns for data products and ML workloads Requirements Strong experience managing data platforms, analytics platforms or MLOps capabilities in an enterprise environment Hands-on experience operating Palantir Foundry, AIP or a comparable modern data platform Strong understanding of production MLOps, including CI/CD, model deployment, monitoring and lifecycle governance Experience supporting production data products or ML models at scale Strong service management experience across incident, change, problem and request processes Experience working with security, risk, governance or compliance teams Strong stakeholder management across data engineering, data science, InfoSec and architecture teams Experience managing suppliers, vendors or delivery partners Nice to Have Cloud experience across Azure, AWS or GCP ITIL or formal service management experience Experience in regulated environments Cloud cost optimisation experience Model risk, responsible AI or AI governance experience Key Skills Palantir, Foundry, AIP, MLOps, Platform Management, Data Platform, Model Deployment, CI/CD, Model Monitoring, Data Governance, Access Controls, Service Management, Incident Management, Change Management, Release Management, Vendor Management, Responsible AI, Cloud, DevOps To apply, please email:

Desired Skills and Experience

Palantir Foundry, Palantir AIP, MLOps, Platform Management, Data Platform Management, Model Deployment, Model Monitoring, CI/CD, DevOps, Data Governance, Access Controls, Information Security, Service Management, Incident Management, Change Management, Release Management, Vendor Management, Cloud Platforms, Machine Learning Operations, Model Lifecycle Management