Machine Learning Engineer

Responsibilities

• Design and implement machine learning models for visually creative applications, including computer vision and generative AI.
• Keep up to date with the latest advancements in machine learning, and apply new technologies to improve our products.
• Collaborate with other engineers and cross-functional members to identify new challenges/opportunities and translate open problems into specific technical problems to work on.

Qualifications

• Experience in training or finetuning deep learning models, preferably in computer vision
• A deep and clear understanding of transformers, self- and cross-attention, ViTs.
• Strong grasp on a deep learning framework like PyTorch, Tensorflow or JAX (we use PyTorch here).
• A MS degree or higher in a related field (machine learning, computer science, etc), or equivalent experience.
• Ability to delve deep into topics and have a fundamental understanding of key concepts in ML. We prefer deep understanding of key concepts over having a shallow knowledge of a wide range of topics. Example of delving deep: you are working with CLIP model and want to visualize the attention maps for each transformer block to understand what’s going on.
• Good communication skills in English.
• Strong knowledge of linear algebra and probability.

Plus

• Experience in generative AI, particularly text to image models, is a great plus. Bonus points if you have experience training adapters (LoRA, ControlNet, IP-Adapter etc) for Stable Diffusion models.
• Has strong analytical skills.
• Has has an artistic side.
• Has experience in computer vision and/or generative AI.
• Published papers or research work related to ML.
• Familiarity with diffusers and diffusion models.