Homeoffice ML Research Engineer — Natural Language Processing
Dynamo AI · Lacaussade, Nouvelle-Aquitaine, · Remote
About the job
- Wish to work on the premier platform for AI safety, compliance and privacy. We provide the fastest end to end solution to deploy research in the real world with our fast-paced team of ML Ph.D.’s and builders, free of Big Tech / academic bureaucracy and constraints
- Are excited at the idea of democratizing and productionizing state-of-the-art research on safe and responsible AI
- Wish to work on scaling and robustifying Dynamo AI’s products through intelligent designs and rigorous implementations
- Are motivated to work at a 2023 CB Insights Top 100 AI Startup and see your impact on end customers in the timeframe of weeks not years
- Care about building a platform to empower fair, unbiased, and responsible development of LLMs and don’t accept the status quo of sacrificing user safety for the sake of ML advancement. Responsibilities
- Be responsible of a vertical for Dynamo AI’s state-of-the-art safety guardrails
- Perform rigorous testing of the product features and ensure seamless integrations with customers’ AI workflows
- Push the envelope by implementing novel techniques that delivers the world’s most performing models. Your work will directly empower our customers to more feasibly deploy safe and responsible LLMs
- Work closely with our policy, product, and engineering teams to ship features to customers
- Deep domain knowledge in Natural Language Processing, especially entity recognition tasks
- Extensive experience in designing, implementing, and maintaining production-ready ML code
- Past experience in leading an end-to-end NLP feature. Including problem formulation, data gathering, training and benchmarking/quality assurance
- Adaptability and flexibility. In both the academic and startup world, a new finding in the community may necessitate an abrupt shift in focus. You must be able to learn, implement, and extend state-of-the-art research in short time-frames
- Preferred: Past experience with NER for PII detection and/or synthetic data generation