# Member of Technical Staff (m/f/d) at Sereact

> Onsite · Switzerland · Staff · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Asereact%3Af585585b-9161-4586-95a6-0b72f052d944 (read 2026-11-04).

## Facts (observed)

- Company: [Sereact](https://alderhq.app/companies/sereact)
- Location text: Zurich; Stuttgart Schockenriedstr. 17
- Where it can be done from (inferred): Onsite · Switzerland (evidence: "Location: Zurich; Stuttgart Schockenriedstr. 17")
- Posted: 2026-10-13 (22 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-03
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/sereact/f585585b-9161-4586-95a6-0b72f052d944
- Skills listed (inferred): PyTorch, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Zurich, n 4): p25 $85k, median $98k, p75 $124k
- H-1B filings at this company for similar roles, FY25: 1 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### Who We Are

We are a rapidly growing embodied AI company revolutionizing human labor. Leveraging cutting-edge robotics and advanced artificial intelligence, we develop transformative technologies that redefine how work is done across multiple industries—empowering businesses to streamline operations, boost productivity, and unlock new possibilities.

### Overview

We are looking for a world-class robotics professionals to join our R&D hub in the Zurich area. In this role, you will be at the forefront of developing Vision-Language-Action (VLA) models that enable robots to understand and interact with the world with unprecedented generalization. You will work on the intersection of large-scale foundation models and real-world robotic execution, bridging the gap between state-of-the-art research and deployed embodied intelligence.

### Your Responsibilities

### Research & Development

Design, implement, and scale VLA models and foundation architectures for robotic manipulation and navigation.

### Scaling Laws & Data

Develop strategies for multi-modal data collection, synthetic data generation, and efficient fine-tuning of large-scale models.

### Algorithm Optimization

Optimize model inference for real-time robotic applications without compromising reasoning capabilities.

### Publication & Visibility

Contribute to the global research community by publishing high-impact papers at top-tier conferences (NeurIPS, CVPR, ICRA, CoRL, etc.).

### Collaboration

Work closely with the Core Robotics and Hardware teams to integrate AI models into our physical platforms.

### Qualifications

### Academic Excellence

PhD or Master’s degree in Computer Science, Machine Learning, Robotics, or a related field, with a focus on Deep Learning and Computer Vision.

### Proven Research Track Record

Significant publications and citations at major conferences such as NeurIPS, CVPR, ICCV, ICRA, IROS, or CoRL.

### Professional Background

Experience working in leading AI research environments

### Technical Mastery

Deep expertise in PyTorch or JAX, experience with Transformers, Diffusion Models, and Large Language Models (LLMs).

### Domain Knowledge

Strong understanding of Vision-Language models and their application to Action/Control loops in robotics.

### Location

### Zurich Area, Switzerland

This role is based in our Zurich office, offering a vibrant ecosystem for robotics and AI.

### What We Offer

Free meals at the workplace.

Flexible working hours and the option to work from home when needed.

Direct collaboration with founders and world-leading AI experts.

Access to large-scale compute clusters and proprietary robotic datasets.

A key role in shaping the future of embodied AI.

Competitive compensation and a relocation package for the Zurich area

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Asereact%3Af585585b-9161-4586-95a6-0b72f052d944 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.