ML Ops Lead

ML Ops Lead Overview

At Anaplan, we are a team of forward-thinkers dedicated to enhancing business decision-making through our innovative AI-powered scenario planning and analysis platform. Our platform serves a prestigious clientele, including Fortune 50 companies such as Coca-Cola, LinkedIn, Adobe, LVMH, and Bayer. We foster a Winning Culture characterized by diversity of thought, leadership at all levels, ambitious goal-setting, and celebration of achievements, big and small. Our operating principles emphasize strategic focus, value-driven actions, and disciplined execution, creating an inspiring environment where employees are supported, developed, and rewarded.

Role Overview

We are seeking a highly skilled ML Ops Technical Lead to take charge of our infrastructure, cost management, and deployment strategies for AI and machine learning models. This role involves managing a talented team of DevOps engineers, maintaining a deeply technical and hands-on approach. Your core responsibility will be to build, scale, and secure the foundational platforms necessary for deploying and supporting machine learning and generative AI models, all while maintaining financial accountability.

Key Responsibilities

• Team Leadership & Collaboration: Lead and mentor a team of DevOps engineers, fostering growth and collaboration with Data Science and Engineering leaders.
• Infrastructure Strategy & Automation: Define the roadmap for AI/ML infrastructure needs and automate provisioning across cloud environments using Infrastructure as Code (IaC).
• MLOps & LLMOps Engineering: Design, maintain, and optimize pipelines and CI/CD frameworks for continuous deployment of models, including large language models.
• GenAI Deployment: Deploy large language models into production, ensuring high availability, low latency, and peak performance for Generative AI applications.
• Financial Operations & Budgeting: Establish FinOps practices to monitor, allocate, and forecast cloud infrastructure costs, especially for GPU and CPU resources.
• Resource Optimization: Implement auto-scaling, spot instances, and down-scaling policies to reduce waste, providing full visibility into the economics of training and serving LLMs.
• Observability & Incident Response: Set up 24/7 incident response protocols, telemetry, and metrics to monitor system health, detect model drift, and oversee data pipelines.
• Data Governance & Security: Enforce strict data governance, security standards, and compliance measures across all AI/ML infrastructure components.

Required Skills & Experience

• Proven experience deploying and supporting machine learning systems in production environments.
• Leadership experience managing engineering teams effectively.
• Hands-on experience with Generative AI and large language model deployment patterns.
• History of reducing cloud spend on large-scale AI clusters through optimization techniques.
• Familiarity with tools like MLflow, Kubeflow, LangSmith, or Phoenix.
• Experience with cloud cost management tools such as AWS Cost Explorer, GCP Cost Management, Azure Cost Tools, Kubecost, or Cloudability.
• Deep understanding of Kubernetes, Docker, and service mesh architectures.
• Proficiency with automation tools like Terraform, Ansible, Jenkins, or GitHub Actions.
• Programming skills in Python, Bash, or Go.
• Knowledge of inference serving frameworks such as Triton Inference Server, vLLM, or Hugging Face TGI.

Our Commitment

We are dedicated to fostering a diverse, equitable, inclusive, and welcoming environment. We believe that embracing different backgrounds and perspectives drives innovation and success. We ensure all individuals, regardless of gender, ethnicity, age, disability, or other protected characteristics, are respected and valued. We also provide reasonable accommodations for candidates with disabilities during the application and interview process.

Beware of fraudulent job offers; Anaplan does not send unsolicited job offers via email or conduct interviews without a proper process. All official communications will come from an @anaplan.com email address. For any doubts about authenticity, contact us at [email protected].

If you are interested in joining our team, you can create a job alert to receive future opportunities or apply directly through our application portal by submitting your personal details, resume, and other required information.

Degree Requirement: Not Specified

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