Come join the company building the security operating model for the age of AI. AI has changed how data is used — and security must change with it. Cyera's mission is to empower businesses to accelerate AI Adoption by defining a holistic approach to securing AI - from data to access to model. Instead of perimeter controls and static policies, Cyera provides a unified control plane that understands relationships between data, access, and behaviors across humans, systems, and AI. Backed by the world’s leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data and AI security.

As we expand our AI-powered capabilities, we are looking for an experienced Senior DevOps Engineer with expertise in ML & AI platforms to build, scale, and operate the ML infrastructure that powers our data intelligence engine. This is a high-impact role that sits at the intersection of ML, infrastructure, and security—responsible for enabling reliable, scalable, and efficient model development, training, deployment, and monitoring.

You will work closely with our Data, AI, DevOps, and Backend teams to architect next-generation ML systems that support large-scale processing, model lifecycle automation, and cloud-native inference across AWS, GCP, and Azure.

Build & Operate ML Infrastructure

• Design, implement, and maintain the infrastructure that enables reliable, scalable ML operations across the organization.
• Maintain core ML platform services such as model registries, artifact stores, monitoring, and observability, enabling experiment tracking and model versioning systems.

Enable Scalable Inference & Automation

• Architect CI/CD processes for ML models, including automated testing, benchmarking, validation, and deployment.
• Integrate ML workflows into our microservices-based platform and multi-cloud architecture.
• Optimize real-time inference performance, cost efficiency, and reliability.

Observability, Reliability & Governance

• Build monitoring, alerting, and logging solutions for model performance, drift, data quality, and system health.
• Work closely with security teams to ensure compliance, governance, and risk mitigation for ML assets.
• Troubleshoot and resolve production issues across distributed systems with petabyte-scale data.

Cross-Team Collaboration

• Partner with Data Scientists and ML Engineers to streamline research-to-production workflows.

• Work with DevOps and Backend teams on resource planning, automation, and cloud infrastructure optimization.

• Participate in architectural POCs and contribute to the evolution of our AI platform.

• 4+ years of experience in MLOps, ML Engineering, DevOps, or infrastructure engineering supporting ML workloads.

• Practical experience deploying machine learning models and LLM Providers in production environments at scale.

• Experience in cloud-native environments (AWS, GCP, Azure) — including compute, storage, networking, and security configurations.

• Hands-on experience with containerized environments and orchestration (Docker, Kubernetes).

• Strong understanding of CI/CD concepts and experience building automated pipelines for ML systems.

• Experience with IaC tools (Terraform, CloudFormation, or Ansible).

• Familiarity with distributed training, GPU scheduling, and high-throughput inference.

• Experience with model monitoring, observability, or model drift detection.

• Experience implementing research & ML tooling for experimentation (MLf Low, Lang Fuse)

• Excellent problem-solving skills and the ability to work in a fast-paced, high-scale environment.

• Strong communication and collaboration skills, with the ability to work across R&D teams.

Advantage:

• Experience with LLM fine-tuning, deployment, or optimization.
• Background in building internal ML platforms or ML tooling.
• Strong Python fundamentals and hands-on experience with ML frameworks (Py Torch, Hugging Face, Tensor Flow).
• Experience managing petabyte-scale data systems.
• Knowledge of vector databases, embeddings, or retrieval pipelines.
• Familiarity with SOC2 / ISO 27001 requirements related to ML workflows.
• Experience in highly scalable SaaS products and/or security products.

Why Join Us?

At Cyera, we care about collaboration, innovation, and agility. We take “teamwork” seriously—with our inclusive and supportive culture at the forefront—and we’re just as serious about nurturing Cyerans to grow, both personally and professionally.

Feel free to apply even if your experience doesn’t tick every box.

We’re building something special here—and we welcome Cyerans with diverse backgrounds, perspectives, and experiences.