Multimodal Foundation Model Engineer — Fusion & Distillation

Startupvalleys; Zürich; Hybrid; CHF 120,000 - 190,000; Full time

Benefits offered by this job

Ownership of shipped products

Competitive equity/salary package

Direct collaboration with PhD founders

International team

Job summary

Laelaps AI in Zürich, Switzerland is hiring a Research Engineer for our Foundation Model (Multimodal Fusion & Distillation). You will architect and optimize LEA to fuse RGB, IR, thermal, lidar inputs into a single token stream, running on real security sites with on-site testing.

You’ll work with our engineering teams to set training, evaluation, and deployment strategies, including on-device inference and fast/slow heads, while advancing state-of-the-art multimodal reasoning in safety-critical

Qualifications

• 4+ years training and fine-tuning large vision or multimodal models, or a PhD plus industry experience.
• Strong PyTorch, comfortable with multi-GPU and multi-node training.
• Hands-on fine-tuning of vision-language models (instruction tuning, parameter-efficient methods, full fine-tunes).
• Experience with knowledge distillation or model compression for deployment.
• Work with video or non-RGB sensors: thermal, infrared, lidar or radar.
• Evaluation discipline and solid software engineering hygiene.

Responsibilities

• Native encoders: adapt the best open vision and point-cloud foundation models to RGB, IR, thermal and lidar, one encoder per sensor, raw stream in.
• Fusion: build the layer that aligns every sensor in time and space into one token stream, trained on time-aligned multi-sensor field data that exists nowhere else.
• Slow head: fine-tune an open frontier vision-language model to reason over fused sensor tokens instead of pictures.
• Fast head: distil a small model from the slow head's calls on our own events, so every frame is seen and only hard cases escalate.
• Evaluation: held-out sites, night and thermal slices, regression gates. A model that is worse anywhere does not ship.
• Training machinery: multi-GPU training, data loaders for multi-sensor clips, experiment tracking and reproducible runs.

Skills

PyTorch

Multi-GPU training

Multi-node training

Vision-Language models

Knowledge distillation

Model compression

Sensor fusion

Video data

Education

PhD in ML/CS or related field

Industry experience

Tools

TensorRT

Job description

Laelaps AI in Zürich, Switzerland is hiring a Research Engineer for our Foundation Model (Multimodal Fusion & Distillation). You will architect and optimize LEA to fuse RGB, IR, thermal, lidar inputs into a single token stream, running on real security sites with on-site testing.

You’ll work with our engineering teams to set training, evaluation, and deployment strategies, including on-device inference and fast/slow heads, while advancing state-of-the-art multimodal reasoning in safety-critical