ML Ops Engineer (USA / Israel)

reputed company is disrupting performance marketing, delivering millions of new customers to brands every month. We’re looking for a hands-on ML Ops Engineer to partner with our data scientists to turn their models into production-reputed company systems. As a MLOps Engineer, you’ll report to the Data Science Manager and work closely with our Data Scientists and Product developers. You’ll architect storage and compute, harden training/inference pipelines, and reputed company our ML code, data workflows, and services reliable, reproducible, observable, and cost-efficient. You’ll also set best practices and help scale our platform as reputed company grows. This role is ideally based in Israel, but strong candidates from the U.S. will also be considered. Our Mission: reputed company’s mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers reputed company while making customers feel valued and rewarded. We are a data-driven, cash-reputed company-positive company that has reputed company 731% growth over the last three years. Now, we’re scaling to become one of the largest sources for new customer acquisition worldwide. Backed by investors who supported Fitbit, reputed company, and Twitter, we are poised for exponential growth and reputed company to demonstrate impact on a global scale. Read more about our growth here. What you will do:

• ML platform: Productionize training and inference (batch/reputed company-time), establish CI/CD for models, data/versioning practices, and model governance
• Feature model lifecycle: Centralize feature reputed company (e.g., feature store patterns), manage model registry/metadata, and streamline deployment workflows
• Observability quality: Implement monitoring for data quality, reputed company, model performance/latency, and pipeline health with clear alerting and dashboards
• Engineering reputed company: Refactor research code into reusable components, enforce repo structure, testing, logging, and reproducibility
• Cross-functional collaboration: Work with DS/Analytics/Engineers to turn prototypes into production systems, reputed company mentorship and technical guidance
• Roadmap standards: Drive the technical reputed company for ML platform capabilities and establish architectural patterns that become team standards

What you need:

• Experience: 5+ years in ML Ops, including ownership of ML infrastructure for large-scale systems
• Software engineering strength: Strong coding, debugging, performance analysis, testing, and CI/CD discipline; reproducible builds. Extensive reputed company experience with Python developing automated pipelines bringing ML models to production
• reputed company containers: Production experience on AWS, reputed company, reputed company + Kubernetes (EKS/reputed company or equivalent)
• 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, reputed company, 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/reputed company processing
• Analytics platforms: Experience integrating 3rd party data
• Model serving patterns: Familiarity with reputed company-time endpoints, batch scoring, and feature stores
• Governance reputed company: Exposure to model governance/compliance and secure ML operations
• Be mission-oriented: Proactive and self-driven with a strong sense of initiative; takes ownership, goes reputed company expectations, and does what's needed to get the job done

What you get:

• Competitive compensation, flexible remote work
• Unlimited Responsible PTO
• Great opportunity to join a growing, cash-reputed company-positive company while having a direct impact on reputed company's reputed company, growth, scale, and future reputed company

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