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Lead machine learning engineering for GenAI security products, translating security research into production models. Responsibilities include LLM fine-tuning, multilingual and multimodal model development, MLOps pipeline optimization, data versioning, monitoring, platform integration, GPU resource management, and mentoring engineers. The role also communicates technical trade-offs, infrastructure costs, latency, and model performance to executives and clients.

Operates and improves cloud and Kubernetes security services, including SIEM integrations, asset discovery, security posture assessments, IAM, network controls, secrets, encryption, vulnerability remediation, detection tuning, incident support, and automation. The role establishes reliability objectives, monitors security pipelines, implements infrastructure-as-code controls, investigates incidents, validates remediation, and coordinates cloud security improvements across teams.

Develop and deploy production-ready Generative AI and LLM applications, including RAG systems, agents, APIs, backend services, and data pipelines. Evaluate models and frameworks, implement monitoring and quality improvements, and integrate AI into products and business workflows. Collaborate with technical and business stakeholders to identify opportunities, rapidly prototype solutions, and scale successful AI systems while optimizing reliability, latency, scalability, and cost.

Owns on-premise and airgapped Kubernetes deployments, upgrades, migrations, troubleshooting, and production infrastructure operations for enterprise and government clients. Manages Kubernetes, etcd, PostgreSQL replication, distributed storage, registries, logging, networking, certificates, and automation. Provides independent on-site incident response, validates changes before production, communicates with stakeholders, writes operational documentation, and travels to secure data centers for deployment and go-live support.

The Partnership Manager at Cymetrics will drive team growth, manage partnerships and client relations, and contribute to revenue through strategic sales efforts.

Design, build, and operate scalable, production-grade ETL/ELT and streaming pipelines, ensuring data quality, lineage, security, and high availability. Implement monitoring, automated remediation, IaC and CI/CD, and support GenAI/LLM-powered analytics and reconciliation in a regulated environment.

The Machine Learning Engineer will focus on model development, fine-tuning, pipelines, and deploying machine learning systems, ensuring robust and scalable solutions for AI products.

Perform red team engagements and penetration tests to find and validate fixes, run client-facing project meetings, develop automated security tools with engineering, improve SaaS security products, and research/publish vulnerability write-ups on the company TechBlog.

Lead and manage marketing campaigns, oversee brand projects, identify industry trends, support copywriting, and coordinate teams for effective execution.

The Marketing Manager will manage marketing campaigns, collaborate with agencies, support copywriting, and ensure quality deliverables while achieving sales targets.