Member of Technical Staff – AI Research Engineer (Image/Video Foundation Models)
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Before you apply
LocationZurich
Also inZurich (Switzerland) or Warsaw (Poland)
Work moderemote · Switzerland, Poland
Typefull-time
SeniorityLead
Experience4+ yrs
DepartmentEngineering
EquityIncluded
Company size11–50 people
PostedMar 30, 2026 · 7mo ago
Verified live1d ago
May no longer be actively hiring
Posted by the company on Mar 30, 2026
At a glanceSummarised by Seekless from the posting.
4+ years of experience with Python
Strong Python and PyTorch skills
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
Hands-on experience with diffusion/flow-based image or video generation, or large-scale generative modeling in adjacent domains
Experience with distributed training at scale (multi-node) and performance tuning (throughput/memory)
Experience building evaluation frameworks (offline metrics + human eval + regression tracking)
Strong intuition for data quality and dataset/labeling tradeoffs for training and captioning
Publications are a plus, but shipped impact and strong technical evidence matter more
Skills
Python
PyTorch
Benefits
Flexible PTO
Visa sponsorship
About GenPeach AI
GenPeach AI is a product-driven research lab building vertical multimodal foundation models for hyper-realistic human generation in image and video – designed for emotionally resonant, human-centered AI experiences. Our goal is to create tools that supercharge human creativity rather than replace it.
We train models from scratch: proprietary datasets at massive scale, novel architectures and training recipes, large GPU clusters, and tight product integration so research ships to users quickly.
We are a deeply technical team of around 10 people. We’re advised by Directors from Google DeepMind and backed by leading AI-focused funds and angels from OpenAI, Meta AI, Microsoft AI, Project Prometheus, and Fal. Collectively, our team, advisors, and angels have contributed to models including Meta’s Imagine/MovieGen and foundation-model work behind OpenAI’s Sora, plus Google’s Veo and Gemini.
About the Team
About the role
You’ll join the research team working across image/video generation and multimodal understanding. You’ll work closely with other Research Engineers and Scientists, as well as Founders and help turn research into scalable training runs, strong evaluations, and production-ready systems.
About the Role
We’re hiring an AI Research Engineer to help build and scale GenPeach’s foundation models end-to-end – from implementing new model ideas and training recipes, to owning the parts of the training stack that determine quality and speed, to pushing models through production constraints.
This is a hands-on, high-ownership role. You’ll write research-grade code that becomes production-critical.
In this role, you will
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Implement and iterate on image/video generative model ideas (architecture, losses, conditioning, sampling, pre-training, distillation, post-training)
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Own training performance end-to-end (distributed training, throughput, memory, stability, debugging scaling failure modes)
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Build the experimentation loop (evals, ablations, reproducibility tooling, reporting, decision hygiene)
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Build and improve VLMs for image/video captioning (data recipes, training strategies, model variants, evaluation)
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Run high-iteration research: read papers when useful, implement ideas, validate empirically
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Create captioning pipelines that improve generation training and product quality
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Partner with inference/product to ship under real constraints (latency, cost, reliability, rollout safety)
Build demos and prototypes to showcase capabilities and accelerate iteration
You might thrive in this role if you
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Love the craft of experimentation: fast iteration, clear ablations, strong evals, and honest conclusions
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Enjoy debugging messy real-world training runs (not just clean demos)
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Can move between research and engineering: write clean code, ship utilities, and improve team velocity
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Take ownership beyond your job description when needed (startup reality)
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Communicate clearly and collaborate well in a small, senior team
Minimum Qualifications
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Strong Python and PyTorch skills (4+ years of experience)
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Experience implementing and training deep learning models (generative models, VLMs, LLMs, vision/video, or adjacent)
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Solid understanding of training dynamics, optimization, and practical debugging
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Ability to drive projects end-to-end with minimal supervision
Preferred Qualifications
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Hands-on experience with diffusion/flow-based image or video generation, or large-scale generative modeling in adjacent domains
•
Experience with distributed training at scale (multi-node) and performance tuning (throughput/memory)
•
Experience building evaluation frameworks (offline metrics + human eval + regression tracking)
•
Strong intuition for data quality and dataset/labeling tradeoffs for training and captioning
•
Publications are a plus, but shipped impact and strong technical evidence matter more
What makes this role unique
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Build frontier image/video models and the VLM captioning systems that power them
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Join a lean, senior team that holds a high engineering + research bar
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Direct product impact: your training runs become real user-facing capabilities
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Benchmark against the best in the world and compete on model quality through what we ship
How we work
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You own outcomes end-to-end and are trusted with real responsibility
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Direct, low-ego communication and fast feedback loops
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Bias toward impact: measure → iterate → ship
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Research discipline: clear ablations, reproducibility, and crisp decision-making
Logistics
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Location: Zurich (Switzerland) or Warsaw (Poland) — onsite or hybrid. If you’re elsewhere, we’re open to remote (team/timezone fit considered).
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Compensation: competitive salary + meaningful equity (level-dependent)
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Interview process: quick screen → 2x technical rounds (practical + systems) → team fit/values
What we offer
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Visa sponsorship (where applicable); we’ll make a strong effort to relocate you to Switzerland or Poland if desired
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Remote-friendly: work fully remote, hybrid, or on-site from our hubs
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Regular offsites and in-person events to collaborate and connect
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Flexible PTO