ABBYY
Enterprise · Document AI
- HQ
- Milpitas, US
- Founded
- 1989
- Size
- 500+
- Website
- abbyy.com
ABBYY currently has 18 active AI-related job listings. The company's hiring is concentrated in roles related to serving infrastructure and data, each accounting for 39% of the active listings. Engineering is the top function for these roles. Over the last 30 days, ABBYY has seen a significant increase in new AI roles, with 13 positions posted, representing a 333% rise compared to the previous 30-day period.
ABBYY currently has 18 active AI-related roles in our index. The most common open titles are: Senior Software Engineer – C# (2), Senior Software Engineer – C++ (2), Senior Software Engineer – C++ and C# (2), Staff Software Engineer (2), Data Engineer. Most positions are in Engineering.
ABBYY's active AI hiring is concentrated in: serving infrastructure (39%), data (39%), agents (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
ABBYY is hiring AI talent in: Hungary (10 roles), India (8 roles).
Job postings at ABBYY most frequently reference: model serving, inference infra, vision, fine tuning, multimodal.
In the past 30 days, ABBYY has posted 3 new AI-related roles. That is a -77% change versus the prior 30 days (13 → 3).
Currently tracking 8 active AI roles, up 82% versus the prior 4 weeks. Primary focus: Serve · Engineering.
Enterprise · Document AI
| Title | Stage | AI score |
|---|---|---|
| Principal Machine Learning Engineer - Model Efficiency Optimization Seeking a Principal Machine Learning Engineer to lead ABBYY's model optimization strategy for document AI at scale. This role involves defining technical direction from research to production, focusing on building efficient, high-performing models. Responsibilities include establishing evaluation frameworks for quality vs. efficiency trade-offs, leading implementation of optimization pipelines, and collaborating with various teams to ensure optimized models meet performance standards. Requires expertise in model optimization techniques, efficient deep learning, VLMs, and Python/PyTorch. | ServePost-train | 9 |
| Senior Machine Learning Engineer, Synthetic Data & Document Understanding This role focuses on building generative pipelines for synthetic data at scale for document understanding tasks. The engineer will design and implement systems to produce high-quality, diverse synthetic training data, develop evaluation frameworks, and ensure the synthetic data improves downstream model performance. Responsibilities include owning the synthetic data generation track end-to-end, driving architectural decisions, and building scalable, cost-efficient pipelines. | Data | 8 |
| Senior Machine Learning Engineer - AI-Assisted Data Annotation This role focuses on designing, building, and owning AI-assisted data annotation pipelines using LLMs and vision-language models to generate high-quality training data at scale for enterprise customers. It involves developing annotation strategies, quality validation systems, and optimizing inference pipelines. | DataPost-train | 8 |
| Principal Machine Learning Engineer, Document AI Data (Tech Lead Manager) 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. | DataPost-train | 8 |
| Senior Machine Learning Engineer, Model Training & Evaluation 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. | Post-trainServe | 8 |
| Staff Machine Learning Engineer Staff Machine Learning Engineer role focused on leading the development and architecture of computer vision and multimodal AI systems for enterprise customers, with a strong emphasis on technical leadership, mentorship, and driving production readiness and scalability. | Ship | 8 |
| Staff Engineer – Data/AI Platform Engineering Staff Engineer role focused on designing and scaling enterprise data and AI platforms, including ML model deployment, inference systems, and data governance, to power intelligent automation solutions for enterprise customers. | ServeData | 7 |
| Staff Software Engineer (AI/ML/ SaaS) Staff Software Engineer to build and scale ABBYY's AI platform, focusing on platform engineering, MLOps, and DevOps. The role involves owning AI service deployment, observation, and evolution in production, with a strong emphasis on Kubernetes, cloud infrastructure, and ML lifecycle automation. Responsibilities include designing and building scalable AI platform services, owning MLOps workflows, building Kubernetes platforms for AI workloads, working on data pipelines, and enabling the end-to-end ML lifecycle. | ServeData | 7 |