ML Ops Lead

ML Ops Lead Overview

Anaplan is looking for a technical leader to guide the infrastructure behind its machine learning and generative AI platforms. This position combines people leadership with deep hands-on engineering, with a focus on building, scaling, securing, and operating the systems that support AI workloads while keeping a close eye on cost and financial accountability.

The role sits within a company that describes itself as a team of innovators helping customers improve business decision-making through an AI-enabled scenario planning and analysis platform. The organization says it serves more than 2,400 global companies, including well-known enterprise brands, and emphasizes a culture built around customer success, ambitious execution, and inclusive teamwork.

What you will do

• Lead a DevOps team that supports AI and ML infrastructure, while remaining actively involved in the technical implementation and day-to-day engineering work.
• Mentor engineers at different career stages and partner closely with leaders in data science and engineering to make sure platform decisions support model development and deployment needs.
• Define and drive the infrastructure strategy for AI and ML workloads, including the roadmap for cloud environments and the use of infrastructure-as-code to automate provisioning.
• Build and improve MLOps and LLMOps pipelines, together with CI/CD systems that support continuous and reliable model delivery.
• Deploy large language models into production and ensure the resulting services are highly available, low-latency, and suitable for GenAI applications.
• Put FinOps practices in place to monitor, allocate, and forecast spending on AI infrastructure, especially where GPU and CPU usage creates significant cloud costs.
• Introduce scaling and efficiency measures such as autoscaling, spot instances, and scale-down policies to reduce waste and improve the economics of training and serving models.
• Make the cost structure of model training and inference transparent so the business can understand the unit economics of LLM workloads.
• Set up incident response processes that operate continuously, supported by telemetry and observability to monitor platform performance, model drift, and data pipeline health.
• Apply strong data governance, security, and compliance controls across the AI and ML platform.

What the company is looking for

• Extensive experience deploying and supporting machine learning systems in production environments.
• Proven ability to lead engineering teams and develop people effectively.
• Hands-on experience with generative AI and production deployment patterns for large language models.
• A history of reducing cloud spend in large-scale AI cluster environments.
• Experience using MLOps-related tools such as MLflow, Kubeflow, LangSmith, or Phoenix.
• Knowledge of cloud cost-management tooling, including AWS, GCP, or Azure cost tools, plus Kubecost or Cloudability.
• Strong background in Kubernetes, Docker, and service mesh technologies.
• Advanced infrastructure automation skills with Terraform, Ansible, Jenkins, or GitHub Actions.
• Programming skills in Python, Bash, or Go.
• Awareness of inference and model-serving tools such as Triton Inference Server, vLLM, or Hugging Face TGI.

Culture and workplace

Anaplan says it values diversity of thought, inclusive behavior, and a working environment where people are respected regardless of identity, background, or personal characteristics. The company states that it hires people for who they are and encourages employees to bring their authentic selves to work.

The posting also says the company provides reasonable accommodations for applicants and employees with disabilities so they can take part in the application or interview process, perform essential job duties, and receive equal employment benefits and privileges.

Additional information

The application process includes standard candidate questions and self-identification forms. The page also contains a fraud warning explaining that genuine Anaplan offers are not sent by email, are only made after a substantial interview process, and should come from official Anaplan communication channels.

Applicants are asked to confirm whether they are legally authorized to work in the country where the role is based and whether they will need visa sponsorship now or in the future.

Degree Requirement: Not Specified

Visa Sponsorship May be