Platform Lead – ML Ops

Platform Lead – ML Ops Overview

Anaplan is looking for a Platform Lead to own the machine learning operations platform, with a focus on infrastructure, deployment strategy, and cost efficiency. The role sits within a company that builds an AI-driven planning and analysis platform used by major global brands, and it is intended for someone who can combine technical depth with people leadership. You will be responsible for helping shape the foundation that supports machine learning and generative AI systems, while also keeping a close eye on financial performance and operational reliability.

What you will do

• Take charge of the ML Ops platform function, guiding the infrastructure and deployment approach that supports machine learning and generative AI workloads.
• Manage a DevOps team and support the growth of both junior and experienced engineers through coaching, direction, and day-to-day leadership.
• Work in partnership with data science and engineering leaders to align platform decisions with product and model delivery needs.
• Define the roadmap for infrastructure that powers AI and ML workloads across cloud environments.
• Use infrastructure-as-code methods to automate the creation and management of cloud resources.
• Build and improve MLOps and LLMOps pipelines, including continuous integration and continuous delivery systems for model deployment.
• Deploy large language models into production and ensure they run with strong uptime, low response times, and dependable performance for GenAI applications.
• Put FinOps practices in place to track, assign, and forecast spending on AI infrastructure, especially where GPU and CPU usage creates significant cost.
• Introduce autoscaling, spot-instance usage, and scale-down controls to reduce unnecessary spend and improve efficiency.
• Make the economics of training and serving LLMs visible so the organization can understand and optimize unit costs.
• Establish incident response, monitoring, telemetry, and observability practices that operate continuously and help detect service issues, model drift, and data pipeline problems.
• Apply strong governance, security, and compliance standards across the AI and ML platform environment.

What the company is looking for

• Extensive practical experience deploying machine learning systems into production and supporting them reliably.
• Proven leadership experience managing engineering teams.
• Hands-on experience with generative AI and the ways large language models are deployed in production.
• A history of reducing cloud spend in large-scale AI environments.
• Experience with ML and LLM tooling such as MLflow, Kubeflow, LangSmith, or Phoenix.
• Knowledge of cloud cost-management solutions, including native tools from AWS, GCP, or Azure, as well as Kubecost or Cloudability.
• Strong background in Kubernetes, Docker, and service mesh technologies.
• Advanced ability with infrastructure and delivery tooling such as Terraform, Ansible, Jenkins, or GitHub Actions.
• Programming skills in Python, Bash, or Go.
• Awareness of inference and serving technologies such as Triton Inference Server, vLLM, or Hugging Face TGI.

Culture, inclusion, and support

The organization describes itself as a team of innovators focused on helping customers make better business decisions through an AI-infused planning platform. It says its culture is built around customer success, ambitious goals, leadership at every level, and celebrating wins of all sizes. The company also states that it values diversity of thought and welcomes people from all backgrounds, including differences in gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability, and citizenship.

It also says that reasonable accommodations will be provided for candidates with disabilities during the application or interview process, while performing essential job functions, and in relation to employment benefits and privileges. The posting notes that candidate information may be reviewed with the help of artificial intelligence or other automated tools during recruitment.

Application and hiring notes

To apply, candidates complete the online application form and submit the requested details, including contact information, resume or CV, LinkedIn profile, and answers to eligibility questions. The form asks whether the applicant is legally authorized to work in the country where the role is based and whether they currently need, or may later need, visa sponsorship from Anaplan. The posting also warns applicants about recruitment fraud and explains that legitimate offers are only made after a full interview process, never by email alone, and that official messages come from an @anaplan.com address.

The role is based in London, United Kingdom.

Degree Requirement: Not Specified

Visa Sponsorship May be