Internship

Veeda AI; Zürich; Hybrid; CHF 17,000 - 28,000; Full time

Job summary

Veeda AI in Zürich offers a hybrid internship with exposure to cutting-edge multimodal world models and Physical AI. You will own a scoped project within ML Performance, AI Infrastructure, ML Operations, Data, Robotics, Simulation, or World Models, guided by a mentor, and deliver a tangible artifact the team can reuse.

Ideal candidates have a Bachelor's or equivalent, strong Python and ML fundamentals, and the ability to work in real systems rather than toy environments.

Qualifications

• You have a Bachelor's degree or equivalent hands-on experience in Computer Science, Engineering, or a related technical field, or you are currently working toward one.
• You have real depth in machine learning fundamentals (optimization, generalization, architectures) or in systems fundamentals (operating systems, networking, parallel computing).
• You program fluently in Python and have built and debugged a non-trivial system end to end, on your own.
• You can name which of our seven areas you want to work in and sketch, concretely, what you would try to build or measure there.
• Nice-to-haves: scalable data pipelines, training infrastructure, or simulation tooling are a plus.
• Nice-to-haves: publications or contributions to research on generative models or robot learning.

Responsibilities

• Own one scoped project in a single area — ML Performance, AI Infrastructure, ML Operations, Data, Robotics, Simulation, or World Models — with a mentor and a deliverable agreed in week one.
• Representative Projects: Profile a step-time regression in a Megatron-Core run, add a task to an Isaac Lab environment suite, build a deduplication pass in Ray Data, or measure drift in a world-model rollout.
• Real Systems, Not a Sandbox: Work in the same repositories, on the same clusters, and against the same data as the rest of the technical staff, not a parallel toy version.
• A Deliverable That Outlives You: Ship one artifact the team keeps using — a dataset, a benchmark, an evaluation, or a tool — and write up what you found and what to try next.

Skills

Python

ML Fundamentals

Systems Fundamentals

Big-picture Thinking

Education

Bachelor's degree or equivalent

Tools

CUDA

Triton

MuJoCo

Ray Data

Job description

About Us

Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.

About Us

Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.

Responsibilities

• Own one scoped project in a single area — ML Performance, AI Infrastructure, ML Operations, Data, Robotics, Simulation, or World Models — with a mentor and a deliverable agreed in week one.
• Representative Projects: Profile a step-time regression in a Megatron-Core run, add a task to an Isaac Lab environment suite, build a deduplication pass in Ray Data, or measure drift in a world-model rollout.
• Real Systems, Not a Sandbox: Work in the same repositories, on the same clusters, and against the same data as the rest of the technical staff, not a parallel toy version.
• A Deliverable That Outlives You: Ship one artifact the team keeps using — a dataset, a benchmark, an evaluation, or a tool — and write up what you found and what to try next.

Requirements

• You have a Bachelor's degree or equivalent hands-on experience in Computer Science, Engineering, or a related technical field, or you are currently working toward one.
• You have real depth in machine learning fundamentals (optimization, generalization, architectures) or in systems fundamentals (operating systems, networking, parallel computing), plus the intuition to know when theory breaks down.
• You program fluently in Python and have built and debugged a non-trivial system end to end, on your own.
• You can name which of our seven areas you want to work in and sketch, concretely, what you would try to build or measure there.

NICE TO HAVE

• You have built or maintained scalable data pipelines, training infrastructure, or simulation tooling.
• You have published or contributed to research on generative models for image, video, or 3D content, or on robot learning.
• You have hands-on experience with GPU kernels (CUDA, Triton), a physics engine (MuJoCo, Newton), or real robot hardware.
• You have contributed to an open-source project that other people use.
• You have self-directed projects, research competitions, or competitive programming results that show how quickly you pick things up.
• You can work hybrid from one of our offices — Toronto, Mountain View, Zürich, or Singapore — for the duration of the internship.