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Staff Machine Learning Engineer (Remote - US) at Jobgether. This position is posted by Jobgether on behalf of Abnormal Security. We are currently looking for a Staff Machine Learning Engineer in United States.. Join a high-impact team driving advanced machine learning systems to protect organizations from evolving security threats. In this role, you'll architect large-scale detection models that power real-time message analysis, shaping the strategic ML direction of a world-class cybersecurity platform. Working at the intersection of deep learning, behavioral analysis, and system design, you’ll lead initiatives that directly defend thousands of global enterprises. This is a unique opportunity to influence foundational AI infrastructure and collaborate with top engineers across the stack.. . Accountabilities:. . Act as a technical leader and domain expert across multiple ML workstreams, mentoring teams and influencing the broader machine learning roadmap.. . Architect scalable, generalizable ML systems that address critical detection gaps, guiding model integration across various types—from heuristics to deep learning.. . Lead strategic initiatives, including global model training infrastructure and cross-team ML platforms.. . Own the full ML lifecycle: data analysis, prototyping, training, production deployment, and performance monitoring.. . Troubleshoot complex model behaviors using a deep understanding of theoretical and applied machine learning principles.. . Design automated retraining and evaluation pipelines to adapt to evolving threats and ensure detection efficacy.. . Collaborate with cross-functional stakeholders to ensure ML solutions are aligned with real-world threats and customer-facing product goals.. . . 8+ years of experience developing impactful, large-scale ML systems in applied environments such as ad tech, fraud detection, or recommendation systems.. . Proven expertise in building, deploying, and optimizing ML models that operate in high-throughput, real-time applications.. . Deep understanding of machine learning theory, including limitations and edge cases of deep learning models.. . Strong hands-on experience across the ML stack: data engineering, model training, experimentation, and deployment.. . Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.. . Demonstrated ability to diagnose and resolve performance issues with complex models.. . Bachelor’s degree in Computer Science, Applied Sciences, or related field.. . Ability to drive architecture-level ML strategy and propose long-term, scalable technical solutions.. . Nice to have:. . MS or PhD in Computer Science, Electrical Engineering, or a related field.. . Experience with MLOps and scalable data pipeline development.. . Track record leading large cross-functional ML initiatives across multiple teams.. . Company Location: United States.