Principal Machine Learning Engineer, ServiceNow
$240.1-420.2k
Plus equity (when applicable), variable/incentive compensation + ESPP
Office located in Santa Clara, CA
Cloud-based digital workflows for enterprises
Be an early applicant
Cloud-based digital workflows for enterprises
1001+ employees
Be an early applicant
$240.1-420.2k
Plus equity (when applicable), variable/incentive compensation + ESPP
Office located in Santa Clara, CA
1001+ employees
Company mission
To transform IT to revolutionize the enterprise.
Role
Who you are
- 15+ years of software engineering experience, including significant technical and engineering leadership responsibility
- Demonstrated experience designing and delivering AI/ML-powered products and platforms in production
- Experience leading technical initiatives spanning multiple teams without direct authority
- Demonstrated ability to design systems that scale to enterprise workloads
- Hands-on experience with frontier LLMs, agent frameworks, retrieval and vector technologies, and model evaluation and observability; probabilistic modeling or graph analytics is a strong plus
- Strong backend engineering experience with distributed systems, APIs, microservices, and cloud-native architectures
- Extensive experience using AI-native development tools and coding agents as part of the software development lifecycle
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience
- Cybersecurity products, or deep familiarity with modern security architectures and security operations, is strongly preferred
- Deep expertise in modern AI/ML with a track record of building production AI systems—LLMs, foundation models, agentic architectures, RAG, retrieval, and model evaluation—alongside probabilistic or ML-driven scoring
- The ability to set a compelling technical vision and drive it across teams, then go deep into architecture and code
- A proven record of turning ambitious, ambiguous ideas into products that scale to enterprise workloads
- An innovator’s mindset—challenging conventional approaches and seizing the openings created by rapidly evolving AI
- Command of distributed systems, APIs, cloud-native platforms, and data or graph systems
- Expert-level Python and modern AI frameworks and infrastructure; experience with Java, Go, or similar languages is valuable
- Executive-level communication: able to articulate a compelling technical vision to engineers, customers, and senior leadership
- Applied depth in security problems—threat detection, vulnerability and exposure management, identity security, risk prioritization, or autonomous remediation—is strongly preferred
- Extensive use of AI-native development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf across the software development lifecycle
What the job involves
- As a Principal ML Engineer, you set the technical vision for exploitability-based security across the portfolio—not just one engine
- You define the hardest modeling problems worth solving, set the direction other staff and senior engineers build within, and represent the work to executives, customers, and the broader engineering organization
- The technical vision and architecture for exploitability-driven security: where the engine goes next, and the class of problems it should solve beyond any single release
- The hardest unsolved modeling problems—how calibrated attack-path probability holds up across environments, how identity and agent surfaces enter the model, and how ground truth feeds back into it
- The engineering standards and architectural direction that multiple teams build within: scalability, reliability, and the scientific rigor of the scoring
- The build-on strategy across the portfolio: what the engine reuses from existing products, what must be net-new, and why
- Set technical direction across multiple teams without direct authority, and turn ambitious ideas into working, enterprise-grade products
- Explore and apply emerging AI to cybersecurity in fundamentally new ways—not simply bolt AI onto existing products
- Represent the team’s technology and innovation with executives, customers, partners, and the broader engineering organization
- Mentor staff and senior engineers, and raise the overall engineering bar through coaching and technical leadership
- Champion AI-native engineering practices, including extensive use of coding agents and autonomous development, testing, evaluation, and operational workflows
- Set the direction for AI safety, security, governance, and guardrails for agentic systems running in production
- The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning
- This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like
Our take
ServiceNow provides cloud-based solutions that define, structure, manage, and automate services for enterprise operations, transforming old, manual ways of working into modern digital workflows. The company was founded in 2004 with a vision to build a cloud-based platform that would enable regular people to route work effectively through the enterprise.
Much as Salesforce enables a company to manage its external clients by keeping a record of all contacts and interactions, ServiceNow promises an internal system to meet the needs of employees. It has succeeded in claiming half the market, setting itself apart from legacy IT service-management software players like BMC Software, Hewlett Packard Enterprise, Cherwell Software and CA Technologies.
The company's success comes from two product traits: simplicity and customisability. ServiceNow's IT tools don't require the IT department to set them up. Once running, they offer a single collection centre for requests, data points and checklists, all of which can in turn be analysed by algorithms to predict needs, flag concerns and measure efficiency.
The company has more than 7,700 customers, including 85% of the Fortune 500 list of the United States' largest corporations. ServiceNow now looks to increase its revenue threefold in the upcoming years and has entered into a 5-year partnership plan with Visa, beginning with the launch of a Visa-integrated dispute resolution solution for issuers. The company is prioritising organic growth over mergers and acquisitions, with a target revenue of $15B, something which its Visa partnership will no doubt aid in achieving.
Freddie
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Mar 2012
$11m
GROWTH EQUITY VC
Feb 2012
$17.9m
GROWTH EQUITY VC
Total funding: $83.8m
Company benefits
- Generous family leave
- Matched donations
- Annual learning stipends
- Flexible PTO
- Competitive retirement plan
- Paid volunteer time
Company HQ
Santa Clara, CA
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