Staff Machine Learning Engineer

Suki AI Suki AI · Vertical AI · Suki HQ · Engineering

Staff Machine Learning Engineer at Suki AI, focused on enhancing NLP capabilities for Suki Assistant and Suki Platform. The role involves leveraging expertise in LLMs, RAG, and evaluation frameworks to improve computational infrastructure, manage datasets, and optimize system performance for real-time clinical documentation automation. Requires end-to-end ownership of AI systems in production and experience building distributed backend services for ML/AI applications.

What you'd actually do

  1. Leverage your NLP expertise to enhance our computational infrastructure and improve our technical approaches and algorithms.
  2. Working directly on the platform powering our domain services, you'll collaborate with cross-functional teams to address NLP challenges and scale our platform for thousands of doctors.
  3. You'll manage and curate large datasets, ensuring data quality and relevance for training and evaluation.
  4. You'll monitor and analyze system performance metrics, identifying areas for optimization and implementing necessary improvements.
  5. By staying updated on NLP and Generative AI advancements, you'll incorporate innovations to maintain our competitive edge, reducing doctors’ administrative burdens and significantly impacting their daily lives.

Skills

Required

  • 7+ years in overall software experience
  • 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, including automated evals, human feedback loops, regression testing, and benchmark design
  • 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

Nice to have

  • Expertise in training models and understanding model suitability
  • Action oriented, with a focus on shipping fast and iterating quickly
  • Creativity in building products using novel approaches and user feedback
  • Problem solving using data and relentless optimization
  • Humility and teamwork
  • Adaptability in a fast-moving organization
  • Confidence in abilities
  • Clear communication and consensus-building

What the JD emphasized

  • shipping AI or machine learning systems to production
  • end-to-end ownership of delivering at least one AI system to enterprise production
  • building and maintaining distributed backend services for ML/AI applications

Other signals

  • Enhance computational infrastructure
  • Improve technical approaches and algorithms
  • Scale platform for thousands of doctors
  • Manage and curate large datasets
  • Monitor and analyze system performance metrics
  • Incorporate innovations to maintain competitive edge