נכון לתאריך
25/11/2025
תל אביב
Noma Security
As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a * * Senior MLOps Engineer * * to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows.
You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale—making ML at Noma reliable, fast, cost-efficient, and production-ready.
This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up.
🛠️ What You’ll Do:
Design, build, and maintain pipelines for * * training, fine-tuning, evaluating, and deploying NLP and LLM models * * across GPU and CPU environments.
Implement automated CI/CD workflows for ML models, including * * benchmarking, testing, performance gating, and production deployment * * .
Select and optimize serving frameworks for * * low-latency, high-throughput inference * * , ensuring reliability and scalability.
Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems.
Monitor and optimize production models for * * performance, cost efficiency, availability, and observability * * .
✅ Requirement for success:
* * 5+ years * * in software engineering, MLOps, or ML engineering with hands-on experience deploying ML models to production.
Strong Python fundamentals and deep understanding of * * transformer architectures * * , tokenization, and NLP frameworks ( * * PyTorch, HuggingFace * * ).
Proven experience deploying and scaling * * LLMs for real-time inference * * —ideally on platforms like * * SageMaker, Vertex AI, or similar * * .
Expertise in * * GPU optimization, distributed training * * , and CPU-based inference optimization.
Strong cloud and Kubernetes background ( * * EKS/GKE/AKS * * , Helm, Terraform, CI/CD for ML).
Experience in fast-paced, early-stage, product-led startups.
Background in building or operating internal ML platforms.
Knowledge of evaluation frameworks for LLM quality, robustness, or observability.
Experience working with * * data-driven ML operations * * , cost optimization, and model observability.
Understanding of security implications in ML pipelines.
Familiarity with multi-model orchestration, vector DBs, or retrieval pipelines.
💙 * * Why Noma? * *
Noma Security is a high-velocity, mission-driven startup shaping the future of * * AI-native data security * * .
As part of a small and highly technical R&D team, your work will directly influence how organizations * * build, deploy, and secure AI systems at scale * * .
You’ll join us at a formative moment—your architecture, tooling, and decisions will shape the ML foundation of the company for years to come.
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