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Senior Machine Learning Engineer, Security (Remote - US)

Senior Machine Learning Engineer, Security (Remote - US)

JobgetherUS
6 days ago
Job type
  • Full-time
  • Remote
  • Quick Apply
Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer, Security in the United States .

As a Senior Machine Learning Engineer in Security, you will leverage advanced ML techniques to detect, prevent, and mitigate security threats, protecting user trust and platform integrity. You will design and implement high-impact models for anomaly detection, behavior analysis, and real-time threat response. Collaborating closely with cross-functional teams, you will help integrate ML solutions into existing workflows, provide actionable insights from complex datasets, and support initiatives to prevent abuse. This role combines hands-on technical development with strategic problem-solving in a fast-paced, high-stakes environment where security and user safety are top priorities.

Accountabilities :

  • Design, develop, and deploy machine learning models to detect and mitigate security threats such as phishing, account takeovers, and malicious content.
  • Build algorithms for anomaly detection, predictive modeling, and adversarial risk detection.
  • Develop graph-based and clustering solutions to identify coordinated malicious activity.
  • Collaborate with Threat Intelligence, Product Trust & Safety, and Security Engineering teams to prioritize and implement ML projects.
  • Integrate ML models into production systems and real-time workflows, ensuring scalability and reliability.
  • Analyze large-scale datasets from multiple sources, including user behavior, telemetry, and external threat intelligence feeds.
  • Participate in initiatives to enhance user safety, including abuse prevention and reputation scoring.

Requirements

  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related technical field.
  • 8+ years of experience designing, building, and deploying ML models for security-focused applications.
  • Strong expertise in anomaly detection, behavior analysis, predictive modeling, and adversarial threat detection.
  • Proficiency in Python, Scala, or Java for ML model development and deployment.
  • Experience with graph-based ML models, clustering techniques, and graph neural networks (GNNs).
  • Familiarity with scalable data systems such as Databricks, Spark, data lakes, and real-time streaming tools (e.g., Apache Kafka, AWS Kinesis, Google Pub / Sub).
  • Knowledge of security domains including phishing detection and account takeover prevention.
  • Strong problem-solving, analytical, and communication skills, with the ability to work collaboratively across teams.
  • Preferred Qualifications :

  • Experience applying ML to real-time threat detection and security solutions.
  • Proven ability to optimize production-level ML systems for high-impact areas.
  • Demonstrated collaboration with cross-functional teams, including engineers, data scientists, and security analysts.
  • Benefits

  • Competitive salary range depending on US zone : $189,000–$287,700 USD.
  • Flexible remote work options across eligible US zones.
  • Comprehensive healthcare, dental, and vision coverage.
  • Retirement plans and employer contributions.
  • Generous PTO and flexible time-off policies.
  • Opportunities for professional development and continuing education.
  • Equity or bonus programs based on company and individual performance.
  • Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

    🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

    📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.

    🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.

    🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

    The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company. Final decisions, interviews, and assessments are then handled by their internal hiring team.

    Thank you for your interest!

    #LI-CL1

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    Senior Machine Learning Engineer • US

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