Senior Solutions Architect – Diffusion AI Models

Role overview We are hiring a Senior Solutions Architect to help AI-native teams design, train, and deploy next-generation image, video, and multimodal generation systems. The role combines deep technical advisory with hands-on optimization across diffusion model architectures and accelerated computing infrastructure. You will act as the technical bridge between a leading generative AI platform and customers building demanding production pipelines across the EMEA region.

Responsibilities

- Guide customer engineering teams through training and deploying diffusion-based image, video, and multimodal generation pipelines on accelerated infrastructure. - Provide deep technical direction on diffusion architectures such as DiT, UNet, and flow matching, including efficient deployment across single and multi-GPU environments. - Optimize the full visual content generation stack, including codec-aware preprocessing, temporal consistency, video token representation, and long-video inference. - Identify performance bottlenecks specific to vision workloads, such as memory-bound diffusion steps, attention scaling at high resolution, and multi-GPU communication patterns for video. - Translate customer insights into actionable feedback for internal research and engineering teams to inform product direction. - Contribute to the EMEA developer community through technical demos, workshops, and reference implementations that showcase platform capabilities.

Requirements

- Master's or PhD in Computer Science, Computer Vision, Machine Learning, or equivalent hands-on experience. - 5+ years of experience in AI/ML with deep specialization in computer vision models. - Hands-on expertise with diffusion model frameworks for image and video generation. - Understanding of vision encoder optimization, VAE architectures, and their inference-time performance tradeoffs. - Strong communication skills with the ability to work effectively alongside ML researchers, creative technologists, and infrastructure engineers.

Nice to have

- Familiarity with inference optimization stacks such as TensorRT, Triton Inference Server, and NIM. - Hands-on experience with video generation techniques including temporal attention, 3D convolutions, or causal video transformers. - Familiarity with codec-aware video pipelines and efficient video tokenization for large-scale generation. - Published research or benchmarks in image/video generation, diffusion acceleration, or visual foundation models.

Benefits and work setup

- Highly competitive compensation with a Poland base salary range of 292,500 PLN to 507,000 PLN, determined by location, experience, and peer pay levels. - Comprehensive benefits package. - Commitment to a diverse, inclusive, and equal-opportunity work environment.