Software Engineer (Machine Learning), Insider Risk - Global Security Organization

he GSO provides industry-leading security and privacy services guided by four principles: trust and transparency, business enablement, risk-informed decision-making, and proactive risk reduction. We strive to build sustainable, world-class security capabilities.

This is a Software Engineer role within Global Security's Insider Risk team. In this role, you are responsible for executing the overall strategy for Insider Risk, from automation and detection development, triage to containment, and remediation of Insider Risk incidents.
There are two major deliverables for the team, automation development and detection engineering. Automation development focuses on ideating and creating tooling solutions and automated workflows to support investigation analysts and remediate crucial Insider Trust issues. Detection engineering focuses on the creation and maintenance of proactive logic to identify insider risks with high fidelity and at scale to prevent harm to users and to the company.

This role will work cross functionally with various business organizations to detect, mitigate, and remediate instances of Insider Risk through:

• Act as a force multiplier across the business by optimizing processes and gaining alignment across stakeholders. A Software Engineer will be responsible for raising the productivity and efficiency of analysts doing manual investigations and remediations.
• Implement data pipelines to support resource efficient model training, validation, and inference in a petabyte-scale environment.
• Help stakeholders identify relevant strategies for mitigating insider threats for users and the business.
• Maintain and support compliant data flows and automation access to allow for interoperability across various business regions.
• Directly contribute to technical projects via committing code, root cause analyses, code reviews, and architecture design.
• Work with cross functional teams globally to ensure alignment, collect feedback on automations, and deploy solutions to get cross functional adoption.

Qualifications

Minimum Qualifications

• Production experience deploying and debugging resource-efficient binary classifiers for anomaly detection
• Experience experimenting with different model architectures
• Experience implementing data pipelines at petabyte scale
• Proficiency in Python and SQL
• Proficiency in algebra/statistics
• Strong technical documentation and reporting skills
• Ability to handle confidential information with discretion

Preferred Qualifications

• Bachelor's degree or industry equivalent work experience in Computer Science or Computer Engineering
• 3+ years of industry experience as a machine learning engineer or machine learning researcher
• Knowledge of common data engineering tooling (e.g. Spark, Kafka) and machine learning approaches (xgboost, SVM, etc.) and popular model architectures (LSTM, Transformers, etc.)
• Knowledge of common training frameworks such as PyTorch, Tensorflow, JAX
• Understanding of security telemetry (i.e. SIEM, EDR, DLP, etc...)
• Working knowledge of cloud platforms (i.e. OCI, GCP, AWS, etc)
• Demonstrates excellent organizational, time management, and problem-solving skills
• Works well within time/budget constraints to solve problems or meet objectives
• Ability to communicate technical concepts to a broad range of technical and non-technical staff

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $156000 - $316800 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.