Staff AI Research Engineer
Build and deploy AI systems (LLMs, bandits) for monetization, balancing revenue and retention. Requires advanced ML degree or equivalent, applied large-model experience, and leadership skills.
Staff AI Research Engineer
Staff-level AI Research Engineer building and deploying bandit and LLM models for monetization, balancing revenue and retention. Requires advanced ML degree or equivalent, applied large-model experience, and leadership skills.
221k – 331kNew York, NYAI ResearchOnsite7+ YOE
About the role
Responsibilities
- Join a full-stack team of frontend, backend, and other AI Research engineers, fostering a collaborative and innovative work environment.
- Contribute to the development and training of bandit models and large-scale neural network models.
- Collaborate with cross-functional teams to understand their needs, to align the models’ outputs with company objectives.
- Participate in and help drive strategic product and business decision-making as a member of the Monetization leadership group.
- Stay up-to-date with the latest developments in machine learning, particularly in LLMs and bandits, and apply this knowledge to drive advancements in our projects.
- Mentor team members, providing guidance and support in their professional development.
- Ensure the delivery of high-quality, scalable, and efficient machine learning solutions.
Requirements
- Proven experience as an AI research engineer, for example, in LLMs, bandits, computer vision, or related fields.
- Strong background in training and fine-tuning large models in an applied setting.
- Advanced degree in Computer Science, Engineering, or a related field with a focus on machine learning or artificial intelligence, or equivalent experience.
- Excellent leadership and communication skills, with the ability to manage and inspire a team.
- Deep understanding of machine learning concepts, frameworks, and best practices.
Nice-to-Haves
- Experience across various machine learning techniques including large language models, multi-armed bandits.
- Experience at all levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, quality evaluations, deployment, and monitoring.
Skills
LLMsMulti-Armed BanditsReinforcement LearningFine-TuningFeature EngineeringMachine LearningNeural NetworksModel DeploymentModel MonitoringComputer Vision
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