Remote Staff Machine Learning Engineer (Remote - US)

Description:

• Join a high-impact team driving advanced machine learning systems to protect organizations from evolving security threats.
• Architect large-scale detection models that power real-time message analysis, shaping the strategic ML direction of a world-class cybersecurity platform.
• Work at the intersection of deep learning, behavioral analysis, and system design, leading initiatives that directly defend thousands of global enterprises.
• Influence foundational AI infrastructure and collaborate with top engineers across the stack.
• 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.

Requirements:

• 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, and a track record leading large cross-functional ML initiatives across multiple teams.

Benefits:

• Base salary range: $229,500 – $270,000 USD.
• Annual performance bonus and equity (RSUs) available for eligible roles.
• Comprehensive medical, dental, and vision insurance.
• Flexible work hours and remote-first culture.
• Paid parental leave and wellness support.
• Home office setup allowance.
• Career growth opportunities within a fast-scaling, AI-driven organization.