Join to apply for the Sr. AI/ML Engineer role at Vectra AI Join to apply for the Sr. AI/ML Engineer role at Vectra AI Vectra is the leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises. The Vectra AI Platform delivers integrated signal across public cloud, SaaS, identity, and data center networks in a single platform. Powered by patented Attack Signal Intelligence, it empowers security teams to rapidly prioritize, investigate and respond to the most advanced cyber-attacks. With 35 patents in AI-driven threat detection and the most vendor references in MITRE D3FEND, organizations worldwide rely on the Vectra AI to move at the speed and scale of hybrid attackers. For more information, visit About Us We're an early-stage startup on a mission to reinvent cybersecurity with AI-native infrastructure. Our vision is to help defenders move faster than adversaries by combining large-scale data, modern AI, and intelligent automation. We're backed by top-tier investors and working with design partners across critical infrastructure and enterprise security. If you're excited about building from the ground up and shaping the future of AI in cybersecurity, we'd love to talk. This is a hybrid role with the expectation of working in our San Jose office 3 days per week. About the Role We're hiring an AI/ML Engineer to design, build, and deploy machine learning systems at the heart of our platform. You'll work on problems like dynamic threat detection, LLM-powered agent reasoning, RAG pipelines, and adversarial behavior modeling. You'll collaborate across research, backend, and security teams to ship high-impact features fast. If you're a hands-on ML engineer who loves shipping smart systems in messy real-world domains, this is for you. What You'll Do Build and fine-tune models for threat detection, anomaly detection, and behavioral modeling (supervised, unsupervised, and semi-supervised). Implement and optimize LLM-powered agents that reason over structured and unstructured security data. Develop RAG pipelines that combine embeddings, vector search, and context injection. Work with streaming and historical security data (logs, events, alerts) to train and evaluate models. Collaborate with backend and platform teams to deploy models in scalable, low-latency environments. Continuously improve model performance, robustness, and explainability. What We're Looking For 3+ years of hands-on experience in applied ML or MLOps (or PhD with practical implementation). Strong ML fundamentals (classification, clustering, anomaly detection, embedding techniques). Experience working with real-world noisy data, ideally in time series, logs, or graph-structured form. Experience with LLMs (e.g., OpenAI, Mistral, Llama), embeddings, and vector databases. Well-versed in techniques for long context (chunking, sliding window, hierarchical summarization). Solid skills in Python, PyTorch or TensorFlow, and ML pipelines. Strong collaboration and ownership mindset—you write clean code, ask great questions, and iterate quickly. Someone who is looking for a hybrid work environment, with a minimum of 3 days in the San Jose office. Nice to Have Familiarity with cybersecurity data (SIEM logs, alerts, EDR telemetry, threat reports). Experience with agent frameworks (LangChain, AutoGen, CrewAI) and agent protocols. Exposure to adversarial machine learning or explainability techniques. Infra skills for ML (Docker, K8s, GPU scheduling, model serving). Why Join Us? Founding-level equity and full-stack ownership. Work on hard, meaningful problems at the intersection of AI and security. High agency, fast learning, direct access to customers and users. Backed by seasoned operators and security leaders. Our competitive total rewards package includes cash compensation within the range provided below. Actual pay for this position may vary based on the hired candidate's location, experience and relevant incumbent pay position. Vectra Total Rewards
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