Staff Software Engineer – AI/ML/SaaS

🕒 April 1

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

ABBYY

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1989

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 Venture Round on 2021-05

Artificial Intelligence • Enterprise • SaaS

ABBYY is a leading provider of intelligent automation solutions, leveraging AI-powered document processing technologies to transform and optimize business processes. The company offers solutions such as ABBYY Vantage, a low-code platform for document processing, and ABBYY Timeline, which provides process mining and simulation to gain actionable insights into business processes. ABBYY serves a wide range of industries including financial services, insurance, and public sector by automating tasks such as accounts payable automation and customer onboarding. Known for its high accuracy and efficiency, ABBYY's technologies enable organizations to enhance productivity, improve process intelligence, and achieve cost savings.

📋 Description

• Design and build scalable AI platform services using Python and microservice architectures • Own DevOps and MLOps workflows including CI/CD, model deployment, versioning, and rollback • Build and maintain Kubernetes-based platforms for AI workloads • Work on data pipelines, dataset versioning, and auto-labeling workflows for model training • Enable end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring • Collaborate closely with ML researchers, product teams, and other platform engineers • Drive best practices in software design, reliability, security, and observability • Lead technical discussions, review designs, and mentor team members

🎯 Requirements

• 10+ years of experience in backend or platform engineering • Strong proficiency in Python (or similar backend languages) • Solid experience building microservices and distributed systems • Hands-on expertise with Kubernetes in production environments • Strong understanding of DevOps and MLOps principles • Experience with data management for ML (datasets, labeling, pipelines) • Cloud experience with Azure or strong willingness to adopt Azure quickly • Ability to think at system level and still deliver hands-on

🏖️ Benefits

• 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.