Staff Software Engineer (ai/ml/ Saas)

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

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.

What you'd actually do

  1. Design and build scalable AI platform services using Python and microservice architectures
  2. Own DevOps and MLOps workflows including CI/CD, model deployment, versioning, and rollback
  3. Build and maintain Kubernetes-based platforms for AI workloads
  4. Work on data pipelines, dataset versioning, and auto-labeling workflows for model training
  5. Enable end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring

Skills

Required

  • Python
  • microservice architectures
  • Kubernetes
  • DevOps
  • MLOps
  • data pipelines
  • dataset versioning
  • auto-labeling workflows
  • ML lifecycle
  • data ingestion
  • model training
  • model evaluation
  • model deployment
  • model monitoring
  • Azure
  • system level thinking
  • hands-on delivery

Nice to have

  • building internal AI/ML platforms
  • model serving frameworks
  • inference optimization
  • weak supervision
  • human-in-the-loop systems
  • enterprise or B2B SaaS environments

What the JD emphasized

  • 10+ years of experience in backend or platform engineering
  • Hands-on expertise with Kubernetes in production environments
  • Strong understanding of DevOps and MLOps principles
  • Experience with data management for ML (datasets, labeling, pipelines)

Other signals

  • build and scale AI platform
  • MLOps
  • Kubernetes
  • ML lifecycle automation
  • production code