Principal Machine Learning Engineer, Document AI Data (tech Lead Manager)

ABBYY ABBYY · Enterprise · India · R&D (Engineering)

Principal Machine Learning Engineer (Tech Lead Manager) to lead ABBYY’s Document AI Data team. This role involves hands-on technical leadership and people management, owning the architecture and roadmap for building high-quality training data at scale, and managing the team. The focus is on defining how training data is created, validated, and scaled for LLMs and VLMs.

What you'd actually do

  1. Own the end-to-end technical strategy for the Document AI data platform, spanning: AI-assisted annotation, Synthetic data generation, Document understanding pipelines
  2. Define architectural principles that unify multiple data workflows into a scalable, cohesive platform
  3. Establish and operationalize standards for high-quality training data in collaboration with Modeling teams
  4. Drive the development of data quality evaluation frameworks, including metrics for coverage, fidelity, and performance
  5. Lead, mentor, and grow a team of Senior Machine Learning Engineers

Skills

Required

  • MS or PhD in Computer Science, Engineering, Mathematics, or related field
  • 10+ years of experience in Machine Learning / AI
  • Large Language Models (LLMs)
  • Vision-Language Models (VLMs)
  • Large-scale data systems
  • Technical leadership
  • People management
  • Building and scaling AI-driven data pipelines
  • Hiring and developing senior engineering talent
  • Prompting
  • Fine-tuning
  • Evaluation for structured tasks
  • Training data quality principles
  • Architecting large-scale data platforms
  • Python
  • PyTorch
  • Cloud platforms
  • MLOps tooling
  • Pipeline orchestration
  • Document AI systems
  • Layout analysis
  • Real-world document variability
  • Leading and inspiring high-performing engineering teams
  • Making long-term architectural decisions
  • Cross-functional collaboration
  • Translating complex technical tradeoffs into clear strategic direction
  • Building teams in ambiguous, fast-scaling environments

Nice to have

  • AI-assisted annotation
  • Synthetic data generation
  • Document understanding pipelines
  • Responsible AI

What the JD emphasized

  • Proven track record as both a technical leader and people manager
  • Experience building and scaling AI-driven data pipelines in production
  • Deep expertise in LLMs and VLMs, including prompting, fine-tuning, and evaluation for structured tasks
  • Strong understanding of training data quality principles (distribution, diversity, and validation)
  • Proven ability to architect large-scale data platforms processing millions of documents

Other signals

  • leading a team
  • architecting data platforms
  • training data for LLMs and VLMs
  • AI-assisted annotation
  • synthetic data generation