Job Description

Picsart is the world’s #1 creative platform with over 100 million creators and 1 billion installs. The mission: make creativity accessible to everyone.



Join a team where your work impacts millions of creators daily and your ideas drive real change.

At Picsart, we bring the wonder of creativity to the world and make it easy. As a Senior ML Scientist on our Generative Computer Vision team, you’ll help invent and deploy breakthrough generative AI capabilities for millions of creators globally. Your work will shape the future of visual expression by building state-of-the-art tools at the intersection of research and real-world impact.

How You’ll Make an Impact:

Invent and publish advanced diffusion, transformer, and multimodal text-to-image/video models, including high-resolution generation (up to 16K). Build innovative features for image/video retouching, effects, quality enhancement, and avatar generation. Develop and optimize training and inference pipelines with use of data parallelism, quantization, distillation, TensorRT. Design, build, and maintain training and evaluation workflows using PyTorch 2.x, DataBricks, and SLURM. Create human-in-the-loop evaluations including side-by-side visual comparisons and technical metrics calculation. Collaborate closely with product, design, and engineering teams to ship research-driven features at scale. Tune/Train custom LLM models for the Picsart AI Assistant (Qwen, LLama, GLM and others).

What You’ll Bring:

Ph.D. (or equivalent research experience) in Computer Science, Electrical Engineering, Mathematics, or a related field. 5+ years of experience delivering computer vision and generative AI models in production. First-author publications or patents in top-tier venues such as CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, or ICLR. Deep expertise in PyTorch and CUDA. Hands-on experience with diffusion models, GANs, and vision-language architectures. Strong foundations in linear algebra, probability, optimization, and large-scale model training techniques (e.g., mixed precision, gradient checkpointing).

Good To Have:

* Contributions to open-source ML/CV projects or toolkits.