ML Engineer – MLOps & Platform Engineering (m/w/d)
Core
Build and operate the MLOps platform and AWS service that manages training data, model lifecycle, and production deployment for a Large Engineering Model (LEM) used in plastic injection molding simulations.
Role type
Senior MLOps Platform Engineer
Builds
Data pipelines, model registry, training workflows, and a scalable AWS inference service for engineering simulations
Domain
Manufacturing simulation / Industrial AI / Cloud Infrastructure
Deliverable
production ML models
Required skills
Python, Software Engineering (CI/CD, Testing), Cloud Infrastructure (AWS), Containerization (Docker, Kubernetes), Experiment Tracking (MLflow, W&B), Data Versioning (DVC)
Preferred skills
Scientific computing, On-prem/Edge deployment, Workflow Orchestration (Airflow, Prefect), Model Optimization (Quantization, Pruning), Infrastructure as Code (Terraform)
Responsibilities
Design data pipelines for versioned and reproducible training; Manage the full model lifecycle from experiment to production; Build monitoring for model drift and data quality; Enable AI engineers with tools for training and evaluation; Operate and scale the AWS inference service; Collaborate with cloud teams on platform rollouts
Seniority
Senior, hands-on IC
