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
25,000-35,000 ₪
Today, more people than ever are speaking publicly about their mental health. Whether it's ourselves, our friends and family or even public figures, taking care of your behavioral health is no longer a taboo, it's vital, and it's only human.
we are on a mission to help deliver the world's most effective behavioral care through data, measurement, and personalization. Or simply put, we want to give clinicians the support they need to do the important work only they can do.
What is this opportunity?
At our company, we build a behavioral health CareOps automation platform that transforms therapy conversations into structured insights and clinical documentation. Our system uses advanced ML and LLM technologies to improve care quality, support therapists daily workflows, and reduce documentation time by over 50%.
As a Senior ML Infrastructure Engineer, you will design and build the infrastructure that powers our ML and LLM systems in production. You will develop scalable pipelines, systems, and tools that enable data scientists and AI teams to efficiently develop, test, and deploy models.
Working closely with data scientists, engineers, and product teams, you will ensure our ML capabilities are reliable, scalable, and production-ready-helping bring cutting-edge AI to improve mental health care.
This is a unique opportunity to join a startup with a real impact on thousands of peoples wellbeing and mental health, applying cutting-edge AI technologies to solve meaningful human problems.
How will you contribute?
Design and build infrastructure and backend services supporting ML and LLM systems
Develop and maintain ML training and deployment pipelines
Build tooling that enables model experimentation, versioning, and reproducibility
Implement CI/CD pipelines for ML workflows and model deployment
Support LLM deployment, prompt management, and optimization pipelines
Improve reliability, monitoring, and observability of ML systems in production
Collaborate with data scientists to productionize models and research prototypes
Ensure secure and compliant handling of sensitive healthcare data
we are on a mission to help deliver the world's most effective behavioral care through data, measurement, and personalization. Or simply put, we want to give clinicians the support they need to do the important work only they can do.
What is this opportunity?
At our company, we build a behavioral health CareOps automation platform that transforms therapy conversations into structured insights and clinical documentation. Our system uses advanced ML and LLM technologies to improve care quality, support therapists daily workflows, and reduce documentation time by over 50%.
As a Senior ML Infrastructure Engineer, you will design and build the infrastructure that powers our ML and LLM systems in production. You will develop scalable pipelines, systems, and tools that enable data scientists and AI teams to efficiently develop, test, and deploy models.
Working closely with data scientists, engineers, and product teams, you will ensure our ML capabilities are reliable, scalable, and production-ready-helping bring cutting-edge AI to improve mental health care.
This is a unique opportunity to join a startup with a real impact on thousands of peoples wellbeing and mental health, applying cutting-edge AI technologies to solve meaningful human problems.
How will you contribute?
Design and build infrastructure and backend services supporting ML and LLM systems
Develop and maintain ML training and deployment pipelines
Build tooling that enables model experimentation, versioning, and reproducibility
Implement CI/CD pipelines for ML workflows and model deployment
Support LLM deployment, prompt management, and optimization pipelines
Improve reliability, monitoring, and observability of ML systems in production
Collaborate with data scientists to productionize models and research prototypes
Ensure secure and compliant handling of sensitive healthcare data
Requirements:
What qualifications and skills will help you be successful?
5+ years of industry experience in ML Infrastructure, Backend Engineering, or related fields
Strong Python experience with production-grade systems
Experience working with cloud platforms (AWS, GCP, or Azure)
Experience with containerization technologies (Docker, Kubernetes)
Experience building CI/CD pipelines for ML systems or backend services
Experience supporting LLM deployment or ML models in production
Familiarity with model versioning, experiment tracking, and ML tooling
Some nice to haves are:
Experience with prompt engineering and prompt management
Experience with data versioning tools (DVC, Pachyderm, etc.)
Experience with MLOps platforms (MLflow, Kubeflow, etc.)
What qualifications and skills will help you be successful?
5+ years of industry experience in ML Infrastructure, Backend Engineering, or related fields
Strong Python experience with production-grade systems
Experience working with cloud platforms (AWS, GCP, or Azure)
Experience with containerization technologies (Docker, Kubernetes)
Experience building CI/CD pipelines for ML systems or backend services
Experience supporting LLM deployment or ML models in production
Familiarity with model versioning, experiment tracking, and ML tooling
Some nice to haves are:
Experience with prompt engineering and prompt management
Experience with data versioning tools (DVC, Pachyderm, etc.)
Experience with MLOps platforms (MLflow, Kubeflow, etc.)
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.
תל אביב - יפו
ערב
7 חודשים
סבסוד
