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
35,000-55,000 ₪
We are looking for a highly skilled and motivated Machine Learning Engineer to join our Data Science Engineering team. The ideal candidate will have a deep understanding of machine learning infrastructure and solutions, enabling data scientists and engineers to efficiently develop, deploy, and maintain models in production by delivering a scalable and high-quality solution. This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams.
What Youll Do:
Develop and maintain machine learning infrastructure and solutions to support the efficient development, deployment, and maintenance of models in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models.
Design and implement software architecture for machine learning solutions.
Optimize model deployment and serving using industry best practices with CPU, GPU, and external APIs.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Collaborate with the DevOps team to establish best practices for MLOps.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning and related technologies.
What Youll Do:
Develop and maintain machine learning infrastructure and solutions to support the efficient development, deployment, and maintenance of models in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models.
Design and implement software architecture for machine learning solutions.
Optimize model deployment and serving using industry best practices with CPU, GPU, and external APIs.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Collaborate with the DevOps team to establish best practices for MLOps.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning and related technologies.
Requirements:
Experience and Skills:
A deep understanding of machine learning infrastructure and solutions.
4+ years of Python programming experience MUST.
3+ years of experience as a Machine Learning Engineer, including experience in deploying machine learning models into production at scale MUST.
Experience with software architecture design
Deep familiarity with industry best practices for optimized model deployment and serving with CPU, GPU, and external APIs.
Background in Linux and containerized environments such as Kubernetes and Docker MUST.
Experience with Cloud
Experience with tools such as ElasticSearch, RabbitMQ, Kafka, and Redis.
Experience with unit testing and CI/CD.
Experience in MLOps Advantage.
Experience working in a production environment and with data science teams Advantage.
Ability to collaborate with the DevOps team around best practices of MLOps Advantage.
Experience with NLP and Speech models Advantage.
Self-motivated, team player, action and results-oriented.
Well organized, with excellent communication and reporting skills.
Experience and Skills:
A deep understanding of machine learning infrastructure and solutions.
4+ years of Python programming experience MUST.
3+ years of experience as a Machine Learning Engineer, including experience in deploying machine learning models into production at scale MUST.
Experience with software architecture design
Deep familiarity with industry best practices for optimized model deployment and serving with CPU, GPU, and external APIs.
Background in Linux and containerized environments such as Kubernetes and Docker MUST.
Experience with Cloud
Experience with tools such as ElasticSearch, RabbitMQ, Kafka, and Redis.
Experience with unit testing and CI/CD.
Experience in MLOps Advantage.
Experience working in a production environment and with data science teams Advantage.
Ability to collaborate with the DevOps team around best practices of MLOps Advantage.
Experience with NLP and Speech models Advantage.
Self-motivated, team player, action and results-oriented.
Well organized, with excellent communication and reporting skills.
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.
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