Scale's mission is to accelerate the development of AI applications. The SGP ML team works on the front lines of this AI revolution, interfacing directly with clients to build cutting-edge products using proprietary research and resources. As an ML Researcher, you'll work with clients to train ML models to satisfy their business needs, ranging from training next-generation AI cybersecurity firewall LLMs to training foundation genomic models making predictions about life-saving drug proteins. There are also various research opportunities on how to apply ML to the forefront of enterprise data.
Requirements
- At least 1-3 years of model training, deployment and maintenance experience in a production environment
- Strong skills in NLP, LLMs and deep learning
- Solid background in algorithms, data structures, and object-oriented programming
- Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
- Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc.
- Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc.
Responsibilities
- Train state of the art models, developed both internally and from the community, in production to solve problems for our enterprise customers.
- Work with product and research teams to identify opportunities for ongoing and upcoming services.
- Explore approaches that integrate human feedback and assisted evaluation into existing product lines.
- Create state of the art techniques to integrate tool-calling into production-serving LLMs.
- Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems.
Other
- PhD or Masters in Computer Science or a related field
- Experience in dealing with large scale AI problems, ideally in the generative-AI field
- Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals
- Strong written and verbal communication skills to operate in a cross functional team environment
