Senior Machine Learning Engineer (AI)

Location: USA - Remote

Salary: $140,000–$215,000 per year, plus potential bonuses and equity grants.

Company

Cybersecurity company building an AI-native platform that protects organizations by processing large-scale security data and helping customers use AI applications safely.

What you will do

• Provide engineering support for data science teams developing high-throughput, low-latency LLM inference.
• Support LLM post-training, rigorous evaluations, data engineering, and custom model implementation.
• Build and maintain data pipelines and scalable customer-facing applications.
• Analyze potential vulnerabilities and gaps while improving product architecture, performance, reliability, and user experience.
• Own changes end to end, including development, testing, deployment, monitoring, logging, and metrics.
• Collaborate with data scientists and engineering teams, contribute to mentoring, and work in an agile environment.

Requirements

• Experience with data engineering and architecture supporting advanced data science use cases.
• Deep understanding of LLM post-training methods and computational architectures.
• Understanding of scalability and distributed systems, including sharding, partitioning, and concurrency.
• Strong engineering practices covering testing, peer code reviews, continuous integration, and resilient architecture.
• Ability to work collaboratively in a test-driven and iterative programming environment while delivering high-quality, unit-tested software.
• Experience using AI technologies to improve decision-making, workflows, efficiency, and business outcomes.

Nice to have

• Applied experience with scalable architectures for LLM post-training or fine-tuning.
• Experience in cybersecurity or intelligence.

Culture & Benefits

• Flexible and autonomous work culture with an emphasis on responsible AI adoption, experimentation, and innovation.
• Comprehensive physical and mental wellness programs.
• Competitive vacation and holidays, plus paid parental and adoption leave.
• Professional development opportunities and employee networks.
• Compensation includes potential bonuses, equity awards, health insurance, and a 401(k).