Senior AI Engineer
$225k - $250k • Remote • Redwood City, CA
Posted 1mo ago
About the job
Suki is building technology that listens, understands, and gets out of the way, allowing clinicians to focus on patient care. Their flagship product, Suki Assistant, uses AI to automate clinical documentation in real-time, significantly reducing administrative time for doctors. The company is expanding its reach through the Suki Platform, an AI infrastructure powering voice-enabled healthcare experiences across various platforms. The Machine Learning team is central to Suki's product innovation, driving advancements in computational infrastructure, technical approaches, and algorithms. This role involves enhancing the platform, collaborating with cross-functional teams to address NLP challenges, and scaling the system for a large user base. The team also focuses on managing and curating large datasets, monitoring system performance, and incorporating the latest NLP and Generative AI advancements to maintain a competitive edge and improve clinicians' daily lives.
Responsibilities
- Leverage NLP expertise to enhance computational infrastructure and improve technical approaches and algorithms.
- Collaborate with cross-functional teams to address NLP challenges and scale the platform.
- Manage and curate large datasets, ensuring data quality and relevance for training and evaluation.
- Monitor and analyze system performance metrics, identifying areas for optimization and implementing improvements.
- Incorporate NLP and Generative AI advancements to maintain a competitive edge.
- Design and implement evaluation frameworks for LLM-based systems.
- Build and maintain distributed backend services for ML/AI applications.
Requirements
- 7+ years of overall software experience, with at least 2+ years focused on shipping AI or machine learning systems to production.
- Demonstrated end-to-end ownership of delivering at least one AI system to enterprise production.
- Strong working knowledge of LLMs, including prompting, orchestration, RAG, context, and cost management.
- Hands-on experience designing and implementing evaluation frameworks for LLM-based systems.
- Experience in building and maintaining distributed backend services for ML/AI applications.
- Strong grasp of CS fundamentals including abstractions, algorithms, probability, data structures, and system design.
- Experience with agentic workflows, SDKs, and tool calling (e.g., Google Agent SDK, Langgraph, Langfuse, Langsmith) is preferred.