Senior Machine Learning Engineer

About the Role:

At Vyro, we are building the next generation of content creation tools. Our products rely heavily on ML and R&D to empower our products. As we have grown we have raised the bar in the ML team to work with people who can build and train the models from scratch and have the intuition to build upon the existing research in the industry. We are envisioning to create one of the most competitive AI Art Generator algorithms, named as Imagine V5. For this purpose we are training one of the largest fine-tunes of the diffusion model and have plans of training over a 10m+ dataset. If you want to contribute to a team of really exceptional and hard working people, and to build the impact in the world. 

As a Machine Learning Engineer, you will play a crucial role in designing, implementing, and maintaining machine learning models and algorithms to solve complex business problems. Your work will directly contribute to the development of cutting-edge AI solutions and the advancement of Vyro’s  data-driven initiatives. 

What You'll Do:

• Engaging in all aspects of the pipeline, including data processing, model training, and fine-tuning, to deliver the final models
• Writing Building complex inference pipelines for the efficient deployment of models
• Optimising and building our infrastructure for improving creasing model performance for and throughput for variety of use cases
• Building complex ML tools by utilising our latest models for users

What We're Looking For: 

• Degree in software/computer science or relevant experience
• At least 3+ year of experience in a similar role
• Exceptional coders who have the previously built/trained ML models
• Previous experience with deployment and optimisations
• Strong grasp, intuition and knowledge of how Machine Learning and Deep Learning works
• Expertise in coding languages like Python, R, or Java, familiarity with machine learning tools and systems such as TensorFlow or PyTorch.
• Excellent knowledge of DSA/DAA and software engineering principles and practices
• Experience with generative models and computer vision 
• Experience with deployment and optimisations