ML Research Engineer — Natural Language Processing

At Dynamo AI, we believe that LLMs must be developed with safety, privacy, and real-world responsibility in mind. Our ML team comes from a culture of academic research driven to democratize AI advancements responsibly. By operating at the intersection of ML research and industry applications, our team empowers Fortune 500 companies’ adoption of frontier research for their next generation of LLM products.As a Machine Learning Engineer - NLP, you will design, develop, and maintain ML code for our products centered around LLM safety and privacy.Join us if you:• 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.

Qualifications

• 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.

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Salary for this position may vary based on several factors, including the candidate's experience, expertise, and the geographic location of the role. Compensation is determined to ensure competitiveness and equity, reflecting the cost of living in different regions and the specific skills and qualifications of the candidate.