About the job
Become a valued member of the ABBYY team, where we embrace your individual work style. With a hybrid work model, a supportive team atmosphere, and rewards that genuinely reflect your contributions, you can concentrate on what truly matters – your personal development while driving our collective success.
At ABBYY, we are devoted to principles of respect, transparency, and simplicity, ensuring that you can rely on us to always make ethical choices.
As a trusted partner in AI and intelligent automation, we tackle complex challenges for our enterprise clients, transforming their operations through innovative solutions. With over 10,000 customers, including numerous Fortune 500 companies, you will contribute to projects for prestigious names such as DHL, Johnson & Johnson, FDA, DMV, PwC, KeyBank, Spotify, and H&R Block.
About the Role
We invite applications for the position of Staff Software Engineer, tasked with advancing ABBYY’s AI platform. This role is pivotal, straddling platform engineering, MLOps, and DevOps. You will take ownership of the development, deployment, observation, and evolution of AI services in a production environment, with a strong emphasis on Kubernetes, cloud infrastructure, and ML lifecycle automation.
This position requires hands-on technical leadership, where you will design systems, write production-ready code, influence architectural choices, and mentor fellow engineers.
Responsibilities:
· Design and implement scalable AI platform services using Python and microservice architectures
· Manage DevOps and MLOps workflows, including CI/CD, model deployment, versioning, and rollback
· Develop and maintain Kubernetes platforms tailored for AI workloads
· Create data pipelines, oversee dataset versioning, and establish auto-labeling workflows for model training
· Facilitate the complete ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring
· Collaborate closely with ML researchers, product teams, and platform engineering colleagues
· Advocate for best practices in software design, reliability, security, and observability
· Lead technical discussions, review designs, and provide mentorship to team members
Qualifications:
· Over 10 years of experience in backend or platform engineering
· Advanced proficiency in Python (or comparable backend languages)
· Demonstrable experience in building and maintaining scalable systems with a focus on performance and reliability
· Extensive knowledge of Kubernetes, cloud services, and MLOps practices
· Proven track record in designing and deploying complex AI solutions
· Strong communication and interpersonal skills to foster collaboration across teams

