Sr. AI/ML Engineer

About the Role

Key Responsibilities

• 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.

Requirements

• 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—writing clean code, asking great questions, and iterating quickly.
• Someone seeking a hybrid work environment with at least 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).

Qualifications

• 3+ years of applied ML or MLOps experience or PhD with practical implementation

Benefits & Perks

• Life insurance, stock options
• Competitive total rewards package including base pay, incentive plan eligibility, and stock options
• Health care insurance, income protection / life insurance, retirement savings plans
• Behavioral & emotional wellness services, generous time away from work, employee recognition programs
• Founding-level equity and full-stack ownership
• Work on meaningful problems at the intersection of AI and security
• High agency, fast learning, direct access to customers and users