Machine Learning Research Engineer

Client: https://miragestudio.ai/

We're building Mirage Studio, a web-application to democratize high end product photography for e-commerce and DTC brands using image generation (diffusion) models.

We're an ambitious team of machine learning researchers and engineers from Harvard and Caltech, and take a highly technical and results driven approach to our work. We are attempting to produce machine learning models that can match, and hopefully exceed, the quality of the best and most creative professional photography for minimal cost at scale. To meet this standard, our work requires pursuing novel approaches to push beyond what is known under the existing body of research. We are fortunate to be in a position where we have the resources to pursue advanced experiments backed by investors like Y Combinator, Hack VC, and Soma Capital, while still being a small team, in ways that are not possible at research institutions and companies.

We're excited to be hiring for our machine learning team. Come join us as we make high end product photography accessible over the internet to businesses anywhere in the world.


Responsibilities:

- Contribute to all phases of machine learning projects from research, conceptualization, design, implementation, testing, and deployment.

- Implement and deploy multi-node GPU training.

- Develop and maintain robust machine learning models using programming languages such as Python, CUDA, and deep learning frameworks such as TensorFlow and PyTorch.

- Stay informed of advancements in machine learning research and apply relevant findings to ongoing projects.

- Translate complex research papers into practical, efficient, and scalable solutions.

- Communicate highly technical concepts effectively and succinctly to team members, clients, and stakeholders.


Qualifications:

- 2 to 10 years of experience in a machine learning intensive role, or in a research capacity.

- Strong experience with Python, CUDA, and deep learning frameworks such as TensorFlow and PyTorch.

- Proven experience in implementing and deploying multi-node GPU training.

- Track record of implementing machine learning based research project(s) end-to-end.

- Ability to read, synthesize, and implement machine learning approaches documented in recent research papers.

- Excellent written and verbal communication skills, with the ability to convey highly technical concepts effectively and succinctly.