Senior MLOps Engineer

About Noma Security

Noma is building the first comprehensive AI Security and Governance Platform, helping organizations adopt AI and LLMs with confidence and control. As AI becomes core to modern enterprises, the company provides seamless visibility and protection across the entire AI lifecycle. The team works at the intersection of AI, security, and cloud, shaping a new category in a rapidly evolving market.

About the Role

As a Senior MLOps Engineer, you will be a core driver in how the product empowers security teams. You will deeply understand customer needs and translate them directly into product features that deliver real value. As the company scales its AIDR product and expands deeper into model-driven security intelligence, you will own the infrastructure, tooling, and operational foundations that power NLP and LLM training, evaluation, and deployment workflows.

You will architect and operate the systems that enable training, fine-tuning, deployment, and monitoring of 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.

Responsibilities

• 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

Requirements

• 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)

Nice to Haves

• 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

Perks & Benefits

• Located in a prime area with easy access to public transportation, near the Hashalom train station and the Light Rail
• Bright, spacious, dog-friendly office
• Team bonding activities, company retreats, happy hours, and holiday gifts
• Pilates classes at the office
• Monthly lunch budget, dinners provided, and a fully stocked kitchen
• Warm, supportive, and people-first company culture
• Pension & Keren Hishtalmut (advanced training fund)
• Global work environment with teams across Tel Aviv, the US, the Netherlands, and London
• Stock options to share in Noma's growth and success