Forward Deployed Engineer – MLOps

About the role

We are looking for a Forward Deployed Engineer specialized in MLOps to own the end‑to‑end production lifecycle of machine‑learning models. You will ensure that validated models are reliably deployed, monitored, optimized and maintained at scale while collaborating closely with data scientists and ML engineers.

Key responsibilities

• Own production serving, CI/CD, deployment and monitoring of ML models.
• Build and maintain model retraining, versioning and deployment pipelines.
• Manage ML infrastructure and optimize cloud costs through FinOps practices.
• Implement observability, alerting, model drift detection and performance monitoring.
• Lead production incident response, troubleshooting and on‑call duties.
• Collaborate with data scientists and ML engineers to design scalable, production‑ready systems.
• Support presales and proof‑of‑concepts by demonstrating production readiness and scalability.
• Mentor engineers on MLOps best practices and communicate cost, performance and reliability trade‑offs to non‑technical stakeholders.

Required profile

• Minimum 6 years of experience in MLOps, ML platform engineering or related roles with proven production ownership.
• Strong collaboration and mentoring abilities.
• Ability to troubleshoot and clearly communicate technical incidents to business stakeholders.
• Willingness to participate in on‑call and off‑hours production support.

Required skills

• CI/CD pipelines and automation.
• Containerization (Docker, Kubernetes).
• Cloud platforms: AWS, Azure or GCP.
• Infrastructure as Code (Terraform, CloudFormation, etc.).
• ML observability and monitoring tools.
• Model versioning, retraining and drift detection.
• FinOps and cloud cost optimization.
• Alerting, SLA management and production incident response.