Appen
Appen
Appen dezvoltă fundația de date care susține produsele și aplicațiile bazate pe inteligență artificială. Înființată în 1996, compania oferă servicii scalabile de-a lungul întregului ciclu de viață al datelor pentru inteligență artificială, inclusiv colectarea și organizarea datelor, ajustarea fină a modelelor și monitorizarea acestora. Activitatea sa combină expertiza umană cu inteligența artificială pentru a ajuta organizațiile să își utilizeze datele mai eficient. Cu experiență în inteligență artificială, consultanță și marketing, Appen sprijină organizațiile care dezvoltă și implementează tehnologii de inteligență artificială în diverse industrii.

Forward Deployed Engineer, GenAI Data — Appen

Design and optimize generative AI data solutions for Appen’s enterprise clients. Lead data quality, validation, automation, and scalable pipeline delivery.

Descriere

  • Collaborate with enterprise clients to design, deploy, and improve generative AI data solutions
  • Take ownership of the quality of delivered datasets
  • Establish project requirements and align stakeholders on measurable success criteria
  • Develop robust annotation guidance and surface actionable quality insights
  • Turn unclear client objectives into well-defined, scalable workflows
  • Produce generative AI datasets that satisfy agreed acceptance and quality standards
  • Specify validation and automation needs to reduce inconsistency, manual review, rework, and validation time
  • Work with engineering to create scalable, reproducible, and observable data pipelines
  • Develop reusable quality frameworks and validation tools for adoption across projects

Cerințe

  • At least three years of experience in a client-facing technical position, such as solutions engineering, solutions architecture, data or technical consulting, or data operations
  • Bachelor’s degree in computer science, engineering, data science, statistics, or a related discipline, or equivalent practical experience
  • Background in generative AI, machine learning, or model-evaluation data, including LLM training, annotation, or evaluation workflows
  • Consultative approach to client problem-solving, with the ability to ask incisive questions and help stakeholders make stronger decisions
  • Ability to use vibe coding tools; Python and SQL proficiency is a plus
  • Comfort working directly with client engineering and machine learning teams

Beneficii

  • Medical insurance coverage
  • Dental insurance coverage
  • Vision insurance coverage
  • Retirement plan options
  • Paid time off
  • Flexible work arrangements
  • Access to tools, resources, and professional development opportunities

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