Quick Summary
packaging, versioning, CI/CD, safe rollout and rollback. Host and run open-weight models and LLMs on CPU and GPU. Build pipelines for datasets, training jobs and evaluation, together with Research.
About the Role
~1 min readIsland’s AI security features run on machine learning models. Some we train ourselves, and some are open-weight models from the community. As an ML Ops Engineer, you will own the path from research to production: packaging, release, serving, and keeping models fast, reliable and cost-efficient. You will work closely with our researchers and backend engineers.
Responsibilities
~1 min read- →Build and run the infrastructure that serves ML models in production, on AWS SageMaker and other cloud platforms.
- →Own the model release flow: packaging, versioning, CI/CD, safe rollout and rollback.
- →Host and run open-weight models and LLMs on CPU and GPU.
- →Build pipelines for datasets, training jobs and evaluation, together with Research.
- →Monitor models in production (latency, errors, quality, drift) and set up alerts.
- →Keep compute costs under control: choose the right instance sizes and track GPU spend.
- →You have taken ML models to production. You don’t need to train models, but you understand how they are built, evaluated and served.
- You have 4+ years in DevOps, platform or backend engineering, with real production ownership
- You have taken ML models to production. You don’t need to train models, but you understand how they are built, evaluated and served.
- You have strong cloud skills, AWS in particular (IAM, S3, networking).
- You have experience with infrastructure as code (Terraform or similar).
- You have built CI/CD pipelines (GitHub Actions or similar) and work with Docker.
- You use AI coding tools in your daily work.
- You are a team player who takes ownership and learns fast.
- Hands-on experience with AWS SageMaker (endpoints, training jobs or pipelines).
- Experience with ML services on other clouds (Azure ML, Vertex AI or similar).
- Experience serving LLMs (vLLM, TGI, Triton or similar) and running GPU instances.
- Experience with model optimization (ONNX, quantization).
- Experience with Kubernetes.
- Experience with ML workflow tools (MLflow, SageMaker Pipelines, Airflow or similar).
You can find information on how we process and protect your personal data in our Candidate and Employee Privacy Notice. For any privacy-related questions, contact us at privacy@island.io.
Location & Eligibility
About this job
- Who can apply
- Israel
- Posted
- Today
Listing Details
- Posted
- November 3, 2026
- First seen
- November 3, 2026
- Last seen
- November 3, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- November 3, 2026
Signal breakdown
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