ML Internship: Deep Learning for Causal Inference

Ethon was built to eliminate the trillion-dollar waste problem in manufacturing. We are the technology leader in Industrial AI, building agentic workflows that help manufacturers optimize cost, quality, and speed of production. We are a fast-growing team driving massive impact in one of the largest and most under-served industries in the world.

We serve the world’s top manufacturers across the globe. From Siemens and Bosch to Lindt and Roche, our customers trust us to make their factories run better. We are backed by leading investors like Index Ventures, General Catalyst, and Earlybird. Our team draws from Google, Meta, Palantir, MBB, and top manufacturing companies, all here for the same reason: giving manufacturers the technology to run every factory at unprecedented productivity.

We are looking for a machine learning intern with strong engineering skills and the drive to turn ambitious ideas into solid, working prototypes.

In this internship you will work at the intersection of modern deep learning and industrial applications like Root Cause Analysis (RCA). Your mission is to explore how deep learning can be leveraged to infer causal structure and drivers of variation directly from factory data. Concretely, you will:

• Investigate modern deep learning approaches for causal inference on tabular data, and evaluate which directions are most promising for industrial settings.

• Design approaches that jointly exploit tabular signals (sensor readings, process parameters, quality measurements) and contextual information in natural language (sensor names, asset hierarchies, process descriptions, other factory metadata) to improve causal discovery and Root Cause Analysis.

• Build the experimental and benchmarking infrastructure needed to compare your prototypes against established causal discovery baselines, on both public datasets and (anonymized) real manufacturing data.

• Work closely with our ML Scientists and engineers to shape the path from prototype to a component that could augment our analytics stack.

First and foremost, we believe in curious people who are eager to learn and grow. If you're passionate about cutting-edge tech and driving major impact in manufacturing, we want to hear from you. Please also reach out if you don't check all the points mentioned here.

Must-Haves:

• Currently pursuing (or recently completed) a BSc or MSc in Computer Science, Data Science, Machine Learning, Math, Statistics, or a closely related field.

• Solid software engineering skills in Python. This internship will involve building non-trivial training pipelines, simulation code, and benchmarking infrastructure from scratch. Subtle bugs in this kind of code silently poison results for weeks, so the bar on code quality is genuinely high.

• Solid grasp of machine learning fundamentals and comfort with the modern ML stack (PyTorch or JAX), with hands-on experience in deep learning beyond coursework.

• Excellent communication skills in spoken and written English.

• Available for a minimum of 6 months (longer is possible).

• Strong motivation to work in a dynamic and fast-paced environment, and to take an idea all the way to a working prototype.

Bonus (any one or more of the following):

• Exposure to deep learning for structured / tabular / time-series data (e.g. TabPFN, TabICL, FT-Transformer, TabNet, or similar).

• Background in causal inference or causal discovery (e.g. PC, GES, NOTEARS, LiNGAM, DoWhy, score-based or diffusion-based approaches).

• Experience with graph neural networks or structured prediction.

• Experience combining textual / semantic information with numerical data (e.g. via LLM embeddings, retrieval, or multimodal architectures).

• Background in classical statistical modeling, Bayesian inference, or probabilistic programming.

• Experience with time-series data from industrial or physical systems.

• Solid open-source contributions or side projects demonstrating the coding bar above.

We don't just work together. We accelerate each other's professional and personal growth. Come and take your engineering career up a notch, at the forefront of industrial innovation!

Additionally, for this internship we offer:

• Direct mentorship from our ML Scientists and engineering team.

• A well-defined, ambitious problem with room to shape the solution yourself.

• On-site work in a modern office in the center of Zürich, with scope for flexible schedules.