Senior AI Research Engineer — Multimodal GenAI (Remote)

GenPeach AI; Zürich; Hybrid; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Visa sponsorship

Remote-friendly

Offsites and events

Flexible PTO

Job summary

GenPeach AI, a research-driven lab in image/video generation and multimodal understanding, seeks an AI Research Engineer to scale foundation models end-to-end. You will implement model ideas, optimize the training stack, and push research into production-ready systems.

You will own experiments, collaborate with a small senior team, and contribute to efficient captioning pipelines while balancing latency and cost considerations.

Qualifications

• Strong Python and PyTorch skills (4+ years of experience).
• Experience implementing and training deep learning models (generative models, VLMs, LLMs, vision/video, or adjacent).
• Solid understanding of training dynamics, optimization, and practical debugging.
• Ability to drive projects end-to-end with minimal supervision.

Responsibilities

• Implement and iterate on image/video generative model ideas (architecture, losses, conditioning, sampling, pre-training, distillation, post-training).
• Own training performance end-to-end (distributed training, throughput, memory, stability, debugging scaling failure modes).
• Build the experimentation loop (evals, ablations, reproducibility tooling, reporting, decision hygiene).
• Build and improve VLMs for image/video captioning (data recipes, training strategies, model variants, evaluation).
• Run high-iteration research: read papers when useful, implement ideas, validate empirically.

Skills

Python

PyTorch

Deep learning

Distributed training

End-to-end ownership

Tools

Diffusion models

Training stack

Job description

GenPeach AI, a research-driven lab in image/video generation and multimodal understanding, seeks an AI Research Engineer to scale foundation models end-to-end. You will implement model ideas, optimize the training stack, and push research into production-ready systems.

You will own experiments, collaborate with a small senior team, and contribute to efficient captioning pipelines while balancing latency and cost considerations.