Machine Learning Engineer, Research
Remote
Applications have closed
Stability AI
Activating humanity's potential through generative AI. Open models in every modality, for everyone, everywhere.About Stability:
Stability.ai is a community and mission driven, open-source artificial intelligence company that cares deeply about real-world implications and applications. Our most considerable advances grow from our diversity in working across multiple teams and disciplines. We are unafraid to go against established norms and explore creativity. We are motivated to generate breakthrough ideas and convert them into tangible solutions. Our vibrant communities consist of experts, leaders and partners across the globe who are developing cutting-edge open AI models for Image, Language, Audio, Video, 3D and Biology.
About the role:
We are looking for Machine Learning engineers who are passionate about generative models and creative applications of AI. In particular, we are looking for people who share our mission of open-source machine learning models; people who do not believe AI models should be controlled by a centralized gatekeeper behind a closed wall, but rather be truly open and in control by all. We want highly creative ML engineers who are motivated to push the boundaries of generative models. You will have access to state-of-the-art high performance computing resources and you will be able to work alongside top researchers and engineers to truly make an impact in the fast growing world of generative AI.
Responsibilities:
- Lead efforts to drive the design development and production of ML systems, and present the solutions to customers
- Work with Research team on developing the next generation of models, where you may assist with areas such as optimization of model training, model tuning, dataset engineering, HPC clusters, tooling, and work on open-source efforts
- Be a strategic thought partner for leaders across the organization on driving business impact through machine learning
- Work on the Commercial side - productioning generative models, and building the infrastructure to serve them at scale, or work to build customized models for commercial applications
- Prototype and productionize model architecture improvements and new features
Qualifications:
- 3+ years working on machine learning projects, including training, fine tuning and refining models
- Experience with Python scientific stack, PyTorch, creating Jupyter/Colab notebooks
- Experience with JAX / TPUs / CUDA-level / JavaScript (TensorFlow.js etc) a plus
- Ability to communicate machine learning concepts and results effectively through writing and visualization
- Experience with training and/or deploying ML models with Amazon AWS (Sagemaker a plus) or Google Cloud
- Experience with building interactive web demos that serve generative ML models
- Experience with the open-source ML ecosystem (HuggingFace, W&B, etc.)
- Experience with Linux and command line tools
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Biology CUDA Engineering GCP Generative AI Generative modeling Google Cloud HPC HuggingFace JavaScript JAX Jupyter Linux Machine Learning ML models Model training Open Source Python PyTorch Research SageMaker TensorFlow Weights & Biases
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