What are the responsibilities and job description for the Senior Machine Learning Engineer position at Raspberry AI?
Why Raspberry AI
Raspberry AI is a category-defining company for retail that brings the best in generative AI to transform retail companies - radically improving the industry’s climate footprint.
We have raised $29M from a16z, Khosla, Greycroft, etc and product market fit with multi-billion enterprise clients.
Role
As Senior/Staff AI Engineer, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed.
Own the training and development of new customer-facing generative AI design models
Build proprietary generative AI models
Work directly with our CEO and founders
Build our engineering organization
Meet with customers to understand their problems and design solutions to address them
Optimize applications for speed and scale
Qualifications
6 years academic or industrial experience with relevant AI research or engineering.
Experience with latest generative AI models and tooling like Stable Diffusion, ComfyUI, DALL-E, Midjourney.
Have a track record of coming up with new ideas or improving upon existing ideas in AI, demonstrated by accomplishments such as first author publications or projects.
Love to ship great products at lightning speed.
Strong programming skills and deep understanding of modern deep learning frameworks.Our current stack is Python and are looking to scale our system and architecture to the enterprise level.
Communicate clearly and effectively.
CS, Engineering, Physics, or Math degree.
Nice to haves
Early engineer at a hyper-growth startup.
Experience at world class AI / engineering organizations.
Experience with running generative AI models in production environments.
Experience building data pipelines.
