עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
45,000-65,000 ₪
Were on the lookout for a hands-on, experienced MLOps Team Lead to help build and grow our team at Riverside. Youll play a key role in driving AI innovation by building fast, scalable, cost-efficient, and reliable ML infrastructure that enables our AI model development across multiple modalities and cloud environments. Youll work closely with AI researchers, software engineers, and DevOps to create smooth ML workflows, manage large-scale GPU clusters, build data pipelines, and ensure everything runs efficiently. Youll also mentor a team, drive a culture of excellence and good vibes, and take ownership of the employee's full lifecycle, from recruitment to growth and development.
Requirements:
6+ years of experience in Backend Engineering / MLOps / Platform Engineering.
BSc in Computer Science, Software Engineering, or related field.
Experience as a Team Lead (or equivalent positions).
Strong software engineering skills in Python and a proven track record in building production-grade, large-scale backend systems.
Hands-on experience in ML pipeline automation and large-scale model deployment.
Deep understanding of Docker, Kubernetes, cloud-native architectures (AWS/GCP) and infrastructure as code (Terraform, Helm, ArgoCD).
Experience with workflow orchestration engines (such as Airflow, Argo Workflows or Temporal).
Experience with distributed processing platforms (Apache Kafka or similar).
6+ years of experience in Backend Engineering / MLOps / Platform Engineering.
BSc in Computer Science, Software Engineering, or related field.
Experience as a Team Lead (or equivalent positions).
Strong software engineering skills in Python and a proven track record in building production-grade, large-scale backend systems.
Hands-on experience in ML pipeline automation and large-scale model deployment.
Deep understanding of Docker, Kubernetes, cloud-native architectures (AWS/GCP) and infrastructure as code (Terraform, Helm, ArgoCD).
Experience with workflow orchestration engines (such as Airflow, Argo Workflows or Temporal).
Experience with distributed processing platforms (Apache Kafka or similar).
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מודיעין-מכבים-רעות
5 חודשים
ערב
