machine learning engineer in digital manufacturing

Role description

Описание:

Protolabs is a digital manufacturing company that brings innovative products to market through digitally enabled custom manufacturing. Its intelligent pricing platform supports real-time quoting for custom-manufactured parts in a two-sided marketplace.

Задачи:

• Develop, improve, and maintain machine learning models for demand and supply dynamics in a digital manufacturing marketplace.
• Build and refine pricing models, including CAD geometry cost estimation, demand forecasting, and partner routing probability models.
• Apply tree-based methods, probabilistic models, and deep learning to new and existing challenges.
• Design, build, and maintain reliable training and inference pipelines on AWS.
• Run offline experiments, including A/B testing and backtesting, to validate model improvements before deployment.
• Collaborate with ML engineers, data scientists, and domain experts in a cross-functional team.
• Translate part geometry, order history, and partner capacity into meaningful model features.
• Monitor production model performance and address drift or degradation.
• Stay up to date with advances in machine learning, pricing, marketplace modelling, and manufacturing intelligence.
• Mentor and support mid-level and junior engineers.

Требования:

• Proven experience building and deploying machine learning models in production environments.
• Strong coding skills in Python or a similar language.
• Experience with PyTorch, TensorFlow, or scikit-learn.
• Solid understanding of supervised and probabilistic modelling, including regression, classification, and uncertainty estimation.
• Experience with feature engineering from structured or geometric data.
• Hands-on experience with ML pipelines, model versioning, experiment tracking, and MLOps tools such as Weights & Biases, Prefect, or Karpenter.
• Comfortable working with messy real-world data and solving ambiguous problems.
• Nice to have: marketplace or pricing models, operations research, econometrics, supply chain optimisation, 3D or geometric data, scaling ML infrastructure, explaining complex models to non-technical stakeholders, ML monitoring, alerting, and retraining workflows.

Условия:

• Annual company bonus.
• Access to OpenUp psychologists and Headspace.
• Dog-friendly office.
• Daily lunch and snacks provided in the office.
• Learning and development days, funding for courses, events, and training.
• Access to the in-house LEARN platform.
• In-house 3D printing.