ML Ops Engineer (USA / Israel)

Nift is looking for a hands-on ML Ops Engineer to partner with data scientists and turn their models into production-ready systems. The ideal candidate will have experience in ML Ops, software engineering, and cloud and container technology.

Requirements

• 5+ years of experience in ML Ops, including ownership of ML infrastructure for large-scale systems
• Strong coding, debugging, performance analysis, testing, and CI/CD discipline
• Extensive commercial experience with Python developing automated pipelines bringing ML models to production
• Production experience on AWS, DataBricks, Docker + Kubernetes
• IaC: Terraform or CloudFormation for managed, reviewable environments
• ML tooling: MLflow/SageMaker (or similar) with a track record of production ML pipelines
• Monitoring/observability: ML monitoring (quality, drift, performance) and pipeline alerting
• Collaboration: Excellent communication, comfortable working with data scientists, analysts, and engineers in a fast-paced startup
• PySpark/Glue/Dask/Kafka: Experience with large-scale batch/stream processing
• Analytics platforms: Experience integrating 3rd party data
• Model serving patterns: Familiarity with real-time endpoints, batch scoring, and feature stores
• Governance & security: Exposure to model governance/compliance and secure ML operations

Benefits

• Competitive compensation
• Flexible remote work
• Unlimited Responsible PTO