What are the responsibilities and job description for the Applied AI Finetuning Engineer position at Menlo Ventures Management, L.P?
About the role
As an Applied AI Finetuning Engineer, you will drive the adoption of frontier AI by developing bespoke and fine-tuned LLM solutions for top enterprises. You’ll leverage your customer-facing engineering experience and technical skills to help customize Anthropic's frontier LLMs to the needs of cutting-edge customer applications.
In collaboration with the Sales, Product, and Engineering teams, you’ll help enterprise partners incorporate leading-edge AI systems into their products. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards.
Responsibilities :
- Design and execute high-quality finetuning projects for critical customers, delivering customized AI solutions with exceptional reliability
- Collaborate closely with ML researchers to develop and implement cutting-edge finetuning techniques
- Leverage advanced machine learning skills to optimize finetuning strategies and enhance model performance
- Partner with account executives to understand customer requirements and develop tailored finetuning solutions
- Serve as the primary technical advisor for customers on finetuning projects, offering guidance on integration, deployment, and best practices
- Stay current with the latest advancements in AI and finetuning techniques for large language models
- Travel occasionally to customer sites for workshops and implementation support
- Establish a shared vision for creating solutions that enable beneficial and safe AI
- Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities
You may be a good fit if you have :
Deadline to apply : None. Applications will be reviewed on a rolling basis.
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