Machine Learning Intern, Autonomy

Gravis Robotics; Zürich; Vor Ort; CHF 17.000 - 23.000; Teilzeit

Zusammenfassung

Gravis Robotics seeks driven ML interns to contribute to the design, testing, and deployment of machine learning models for autonomous heavy machinery. You will work within the Autonomy team, designing experiments, benchmarking models, and helping define metrics and data requirements for robust performance.

The role emphasizes autonomous problem solving, collaboration, and hands-on development with PyTorch, Python, and robotics tools in a dynamic startup environment.

Qualifikationen

• Proficiency with Python, and Git.
• Familiarity with popular deep learning libraries (PyTorch, etc.).
• Experience with data analysis, ML optimization, and hyperparameter tuning.
• Strong analytical and problem-solving skills, with the ability to interpret experimental results and draw sound conclusions.

Aufgaben

• Design, test, and deploy novel ML models for autonomous heavy machinery
• Benchmark and analyze model performance, including conducting ablation studies to evaluate key design choices.
• Help define performance metrics, validation methodologies, and explore anomaly detection methods to understand the limitations of each architecture and which kind of data is needed for robust performance of the ML models.
• Collaborate closely with the rest of the teams to improve the reliability and scalability of the ML pipeline.

Kenntnisse

Python

Git

Data analysis

Analytical thinking

Problem solving

Tools

PyTorch

NVIDIA Isaac Sim

ROS/ROS 2

C++

Jobbeschreibung

Gravis Robotics is a startup that turns heavy construction machines into intelligent and autonomous robots. Our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of machines in a gamified environment—from anywhere in the world. Our team has over a decade of academic experience honing the cutting edge of large-scale robotics, and is rapidly growing to bring that expertise into a trillion-dollar industry through active deployments with market leaders.

About The Job

We are looking for passionate, skilled interns with a background in machine learning to join our team—and to actively contribute to the development and deployment of extraordinary construction robots. The ideal candidate should be self-motivated, capable of working autonomously in a team and have a strong desire to solve exciting, challenging, and applied problems.

As part of the Autonomy team, you will focus on designing, testing, and benchmarking machine learning models, as well as conducting ablation studies to understand their performance and limitations. The insights generated through your work will help improve these models and support downstream applications, e.g. control policy synthesis, ultimately contributing to faster and more accurate machine digging.

What You Will Do

• Design, test, and deploy novel ML models for autonomous heavy machinery
• Benchmark and analyze model performance, including conducting ablation studies to evaluate key design choices.
• Help define performance metrics, validation methodologies, and explore anomaly detection methods to understand the limitations of each architecture and which kind of data is needed for robust performance of the ML models.
• Collaborate closely with the rest of the teams to improve the reliability and scalability of the ML pipeline.

Qualifications

• Proficiency with Python, and Git.
• Familiarity with popular deep learning libraries (PyTorch, etc.).
• Experience with data analysis, ML optimization, and hyperparameter tuning.
• Strong analytical and problem-solving skills, with the ability to interpret experimental results and draw sound conclusions.

The following experience is considered a plus:

• Model-based reinforcement learning.
• Large-scale robotics simulation environments, such as NVIDIA Isaac Sim.
• Robot Operating System, including ROS or ROS 2.
• C++.

Gravis is an equal opportunity employer. We are committed to building an inclusive and diverse team, and do not discriminate based upon race, color, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics.

We are an international team that is working to solve problems with a global impact: to facilitate efficient communication and collaboration, proficiency in English is a requirement for all roles.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.