ML Engineer training diffusion models for Hapiko’s voice - activated Stickerbox, which turns kids’ spoken ideas into stickers. Bringing Spin Master characters into production safely and on - model.
About the role
- Senior AI/ML Engineer leading development of LLM-based systems and NLP pipelines remotely. Collaborating with founders and shaping technical direction in an ambiguity-friendly environment.
Responsibilities
- Lead the design and development of machine learning systems and LLM-based applications
- Fine-tune and adapt large language models for domain-specific use cases
- Build NLP pipelines to extract structured data from complex, unstructured documents
- Translate ambiguous product goals into clear technical and ML execution plans
- Work directly with product signals, user feedback, and backlog input to prioritize development work
- Build evaluation systems to measure model performance and detect regressions
- Design automated benchmarking pipelines for continuous model testing
- Define meaningful performance metrics tied to real-world outcomes
- Build feedback loops that use user corrections to continuously improve model performance
- Apply computer vision techniques to extract data from PDFs and scanned documents
- Develop AI agents that interact with web systems using automation tools such as Playwright or Selenium
- Work across system design, infrastructure, training, and inference pipelines
- Build scalable ML systems and supporting infrastructure from the ground up
Requirements
- 6+ years of Python development experience
- 4+ years of experience in AI/ML engineering roles
- Strong experience building and deploying LLM-based systems (e.g., Claude, OpenAI models)
- Comfortable using modern LLM workflows such as prompting, evaluation, and iteration
- Experience building NLP systems for information extraction or document understanding
- Strong understanding of model evaluation, benchmarking, and performance measurement
- Experience working with JavaScript/Node.js and React in production environments
- Familiarity with MongoDB and AWS
- Experience building systems that integrate feedback loops or continuous learning
- Comfortable working in ambiguous environments without fully defined specifications
- Strong communication skills (upper intermediate or higher English)
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
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