Senior Machine Learning Engineer, Model Training & Evaluation

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

Senior Machine Learning Engineer responsible for the end-to-end training and evaluation cycle of document AI models, focusing on creating reliable, reproducible, and scalable experimentation pipelines. The role involves designing and maintaining evaluation frameworks, optimizing training processes, and collaborating with platform engineering for infrastructure support.

What you'd actually do

  1. Own the end-to-end training pipeline, including data ingestion, orchestration, checkpointing, and result logging
  2. Design and maintain comprehensive evaluation and benchmarking frameworks
  3. Execute large-scale experiments with strong emphasis on reproducibility and traceability
  4. Analyze results to identify patterns in model performance and quality trade-offs
  5. Implement and validate new optimization techniques and training objectives in collaboration with senior ML leadership

Skills

Required

  • Python
  • PyTorch
  • distributed training frameworks (e.g., DeepSpeed, FSDP)
  • model optimization and compression (e.g., quantization, pruning)
  • evaluation methodology and benchmark design
  • experiment tracking and reproducibility practices
  • training and evaluating large-scale language and/or vision-language models
  • building evaluation frameworks and benchmarking systems
  • model optimization or efficient training techniques

Nice to have

  • vision-language model architectures
  • document AI challenges

What the JD emphasized

  • end-to-end training and evaluation cycle
  • model training and evaluation
  • large-scale experiments
  • evaluation and benchmarking frameworks
  • model optimization
  • distributed training frameworks

Other signals

  • end-to-end training and evaluation cycle
  • document AI models
  • large-scale experiments
  • model improvements are measurable and production-ready
  • applied ML research and production-grade engineering