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Senior Machine Learning Engineer, Model Training & Evaluation
ABBYYSenior Machine Learning Engineer at ABBYY developing training and evaluation pipelines for document AI models. Collaborating with teams to ensure scalable, production-ready experiments and optimizations.
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Own the end-to-end training pipeline, including data ingestion, orchestration, checkpointing, and result logging
- Execute large-scale experiments with strong emphasis on reproducibility and traceability
- Investigate training instabilities, loss anomalies, and performance gaps, providing structured analysis and hypotheses
- Implement and validate new optimization techniques and training objectives in collaboration with senior ML leadership
- Continuously improve pipeline efficiency to reduce iteration time while maintaining experiment quality
- Manage compute resources across parallel experiments, balancing throughput and cost efficiency
- Design and maintain comprehensive evaluation and benchmarking frameworks
- Define clear success metrics across accuracy, latency, memory usage, and domain coverage
- Build automated evaluation pipelines to detect regressions across model checkpoints
- Analyze results to identify patterns in model performance and quality trade-offs
- Partner with Data teams to ensure improvements in training data translate to measurable gains
- Maintain and evolve benchmarking methodologies aligned with industry best practices
- Partner with Platform Engineering on distributed training infrastructure and experiment tracking systems
- Develop internal tooling to support model analysis and research workflows
- Contribute to team standards around reproducibility, experiment tracking, and documentation
- Collaborate with Platform teams to support model deployment, optimization, and serving.
Requirements
What you’ll need- MS or PhD in Computer Science, Engineering, Mathematics, or related field
- 5+ years of experience in Machine Learning, Applied AI, or related areas
- Proven experience training and evaluating large-scale language and/or vision-language models
- Strong background in building evaluation frameworks and benchmarking systems
- Experience with model optimization or efficient training techniques
- Deep understanding of model optimization and compression (e.g., quantization, pruning)
- Strong proficiency in Python and PyTorch, including distributed training frameworks (e.g., DeepSpeed, FSDP)
- Experience managing large-scale training runs (job scheduling, checkpointing, fault tolerance)
- Expertise in evaluation methodology and benchmark design
- Familiarity with vision-language model architectures and document AI challenges.
- Proven ability to independently own complex technical workstreams
- Strong collaboration skills in cross-functional, research + engineering environments.
- Rigorous problem-solving approach with focus on root cause analysis.
- Clear and concise communication of technical findings and experimental results.
Benefits
Comp & perks- Comprehensive medical, accidental, and life insurance
- Weekly wellness sessions to support your physical and mental well-being
- A generous paid time off policy
- We provide remote and hybrid working options to fit all lifestyles.
- We use flexible hours across most of our teams to allow you to find your own definition of balance.
- Encouraging a culture of giving, we provide two paid volunteering days off every year so you can take time to contribute to the causes you care about.
- To ensure your family is cared for, we offer paid parental leave in all our locations.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Machine LearningApplied AIevaluation frameworksbenchmarking systemsmodel optimizationmodel compressionPythonPyTorchDeepSpeedFSDP
Soft Skills
collaborationproblem-solvingcommunicationindependent workstructured analysis
Certifications
MS in Computer SciencePhD in Computer ScienceMS in EngineeringPhD in EngineeringMS in MathematicsPhD in Mathematics