Staff Machine Learning Engineer

Description

The Security and Risk Engineering group builds AI-driven security tools that lower risk for the company and its customers.

The team is starting a new exposure analysis tool from scratch. It ranks security issues by how exploitable they are, meaning how realistically an attacker could get in, instead of by raw severity. The design is still changing, and this role helps decide what a good design looks like.

Responsibilities

• As Staff ML Engineer, you take end-to-end ownership of one major part of the exploitability engine, such as the probability core, the exposure graph with entity resolution, or the calibration and validation loop. You make the design choices in that area and carry them into production.
• Own the subsystem from design through delivery and quality.
• Make the design decisions inside your subsystem and define how it connects to the rest of the engine.
• Treat entity-resolution accuracy, calibration quality, and path-ranking precision as primary targets you are accountable for.
• Set technical direction for the engineers working in your area.
• Lead design and code reviews, and raise the engineering standard across the team.
• Mentor engineers and drive a workstream through influence rather than authority.
• Work with product, security R&D, and SecOps to turn customer problems into subsystem designs.
• Set AI safety, security, and guardrail practices for the agentic components of your subsystem.

Requirements

• Expert-level Python and/or Java, Go, or TypeScript.
• 6+ years of software engineering experience, including leading the design and delivery of complex production components.
• Proven track record as the technical owner or lead of a significant system or subsystem in production.
• Hands-on depth in agentic and LLM systems, or in probabilistic or ML-driven scoring such as graph modeling, calibration, search, and optimization.
• Experience building AI/ML production systems. Probabilistic modeling, graph analytics, or calibration and evaluation: strong plus.
• Modern AI experience with RAG, embeddings, vector search, agentic workflows, model evaluation, or AI observability.
• Strong programming skills in Python and/or Java, Go, or a similar language.
• Working knowledge of cloud-native technology, distributed systems, APIs, databases, and scalable architectures.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience.
• Core skills: Predictive Modeling, Graph ML, Security Analytics, Anomaly Detection, Risk Scoring, LLMs/Agentic AI, and MLOps. These lean toward advanced machine learning and AI engineering more than conventional software development.
• Judgment to make sound design calls under uncertainty within your area.
• Technical leadership that moves a workstream forward through influence.
• Cybersecurity or security product experience, or familiarity with modern security architectures and operations: strongly preferred.
• Applied interest in security problems such as attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response: preferred.
• Experience with AI-assisted development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf: a plus.
• Experience with AI evaluation, safety, governance, or policy guardrails: a plus.

Conditions

Base pay for this location is $176,100 - $308,200. This range is a guideline. Individual pay depends on qualifications, skill level, competencies, and work location, and pay is set by where the role is located and may change with that location.

Equity is offered when applicable, alongside variable or incentive compensation.

Sales positions generally use an On Target Earnings incentive structure.

Work setup is assigned by the nature of the job and your work location, and may be flexible, remote, or in-office. The company may use a third-party service to measure the distance between your home and the nearest office to determine eligibility.

Benefits

• Health plans, including flexible spending accounts.
• 401(k) plan with company match.
• Employee stock purchase plan (ESPP).
• Matching donations.
• Flexible time away plan.
• Family leave programs.