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
Requirements
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.
Tech Stack
AWS
Python
PyTorch
Scikit-Learn
Tensorflow
Benefits
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!