Senior Machine Learning Engineer

What you'll do

• Develop, improve, and maintain machine learning models that capture demand and supply dynamics in a digital manufacturing marketplace
• Build and refine pricing-related models, including cost estimation from CAD geometry, demand forecasting, and partner routing probability models
• Apply a range of ML techniques such as tree-based methods, probabilistic models, and deep learning to solve both 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 closely with ML engineers, data scientists, and domain experts in a cross-functional team.Translate complex marketplace inputs like part geometry, order history, and partner capacity into meaningful features for models
• Monitor model performance in production and proactively identify and address drift or degradation
• Stay up to date with advancements in machine learning, especially in pricing, marketplace modelling, and manufacturing intelligence
• Mentor and support mid-level and junior engineers within the team

What it takes

• Proven experience building and deploying machine learning models in production environments
• Strong coding skills in Python (or similar), with experience using ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Solid understanding of supervised and probabilistic modelling, including regression, classification, and uncertainty estimation
• Experience with feature engineering from structured and/or geometric data
• Hands-on experience with ML pipelines, model versioning, experiment tracking, and MLOps tools (e.g. Weights & Biases, Prefect, Karpenter)
• Comfortable working with real-world, messy data and solving ambiguous problems

Nice to have

• Experience with marketplace or pricing models (e.g. demand modelling, price elasticity, cost estimation)
• Background in operations research, econometrics, or supply chain optimisationExperience working with 3D or geometric data (e.g. CAD, point clouds, mesh processing)
• Experience designing and scaling ML infrastructure for production systems
• Strong communication skills with the ability to explain complex models to non-technical stakeholders
• Experience with ML monitoring, alerting, and retraining workflows

Why Protolabs?

• Part of our incredible journey is clearly down to our amazing team, and we strongly believe in giving people a space to truly, authentically be themselves. We also believe that treating our employees well and sprinkling a great place to work with some nice perks can make work a little sweeter.
• Annual company bonus. We celebrate success together! Employees are not only rewarded for their achievements but also for contributing to the overall success of the business.
• Wellness and well-being with access to OpenUp psychologists, practice mindfulness with Headspace and tons more.
• Doggo-friendly office. We are big pet lovers and fully encourage hanging out with your (and your colleagues’) furry friends in the office
• Daily Lunch and snacks are provided in the office; it's a moment for our teams to connect and recharge. Shared meals strengthen our bonds and fuel collaboration.
• We offer learning and development days to be used for training or on volunteering, money to spend on learning courses, events, trainings, Access to our in-house LEARN platform with diverse courses, training, and workshops, In-house 3D Printing and much more!
• Follow us on Instagram to see what Life at Protolabs is all about!