ML Ops Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇮🇱 Israel – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nift

WebsiteLinkedInAll Job Openings

11 - 50 employees

📣 Marketing

💼 Consulting

📦 Logistics

💰 $16.5M Series A on 2018-03

Marketing • Consulting • Logistics

Nift is a technology company that acts as a matchmaker between customers and businesses. By creating a network that connects great customers with outstanding businesses, Nift aims to help both parties thrive. The company offers gifts to potential customers, encouraging them to experience and discover new businesses they may love.

📋 Description

• Productionize batch and real-time training and inference • Establish CI/CD for models, data/versioning practices, and model governance • Centralize feature generation and manage model registry/metadata • Streamline model deployment workflows • Implement monitoring for data quality, drift, model performance/latency, and pipeline health • Create clear alerting and dashboards • Refactor research code into reusable components • Enforce repository structure, testing, logging, and reproducibility • Collaborate with data scientists, analysts, and engineers to turn prototypes into production systems • Provide mentorship and technical guidance • Drive the technical vision for ML platform capabilities • Establish architectural patterns and team standards • Report to the Data Science Manager

🎯 Requirements

• 5+ years in ML Ops, including ownership of ML infrastructure for large-scale systems • Strong coding, debugging, performance analysis, testing, and CI/CD discipline • Reproducible builds • Extensive commercial experience with Python developing automated pipelines bringing ML models to production • Production experience with AWS, DataBricks, Docker, and Kubernetes (EKS/ECS or equivalent) • Experience with Terraform or CloudFormation • Experience with MLflow/SageMaker or similar production ML tooling • Experience with ML monitoring for quality, drift, and performance, plus pipeline alerting • Experience with large-scale batch/stream processing using PySpark, Glue, Dask, or Kafka • Experience integrating third-party data • Familiarity with real-time endpoints, batch scoring, and feature stores • Exposure to model governance/compliance and secure ML operations • Excellent communication and ability to work with data scientists, analysts, and engineers in a fast-paced startup • Proactive and self-driven, with strong initiative and ownership

🏖️ Benefits

• Competitive compensation • Flexible remote work • Unlimited Responsible PTO • Opportunity to join a growing, cash-flow-positive company with direct impact on Nift's revenue, growth, scale, and future success