Related skills
llms rag ml pipelines prompting embeddings📋 Description
- Lead the design and delivery of AI-powered product features from idea to production
- Build LLM-based systems for coaching insights and real-time recommendations during calls
- Architect systems that support low latency and large-scale AI use cases
- Define and implement AI and ML best practices across the engineering org
- Partner with Product and Engineering to identify high-impact AI opportunities
- Build scalable data and feature pipelines to support AI use cases
🎯 Requirements
- 7+ years of software engineering experience with hands-on AI and ML experience
- Proven track record of shipping AI and ML systems into production
- Experience building and deploying ML pipelines for training, inference, monitoring, and improvement
- Deep experience with LLMs and AI tooling, including prompting, RAG, embeddings, agents
- Experience training and fine-tuning models for domain-specific use cases
- Strong system design skills and ability to build scalable, reliable AI systems
🎁 Benefits
- Remote-first, distributed team
- Equal opportunity employer
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