Sr. Machine Learning Engineer

Mix Mode is a leading provider of AI-powered cybersecurity solutions at scale, pioneering a patented third-wave, context-aware AI approach that automatically learns and adapts to dynamic environments. The Mix Mode platform delivers self-supervised, real-time threat detection for known and unknown threats across cloud, hybrid, and on-premises environments. Large organizations with big data workloads – including those in enterprise, critical infrastructure, US Department of War and US Intelligence Community – trust Mix Mode to defend their most important assets.

Backed by PSG and Entrada Ventures, Mix Mode is headquartered in Santa Barbara, California.

Learn more atwww.mixmode.ai .

Mix Mode is looking for a Sr. Machine Learning Engineer to aid in building large-scale, production-grade AI systems for cybersecurity. As a Senior Machine Learning Engineer, you will design, build, and operate distributed systems that apply machine learning to petabyte-scale streaming data. This role combines machine learning with systems engineering. You will be responsible for ensuring that ML systems are reliable, scalable, and performant in production, while enabling fast, reproducible evaluation of model performance.

You will work closely with researchers and engineers to bring models into production and continuously improve their behavior at scale.

• Design and operate production ML systems for large-scale, streaming data
• Own system reliability, performance, and observability in production environments
• Improve the speed and reproducibility of model evaluation and iteration
• Collaborate with researchers to product ionize models and integrate them into distributed systems
• Contribute to the evolution of existing ML systems and infrastructure to improve scalability, maintainability, and performance

• Ability to travel to our office in Santa Barbara, CA, a few times per year
• 5+ years of experience with Python in production environments
• 5+ years of experience applying machine learning using libraries such as PyTorch, scikit-learn, pandas, etc.
• Experience building and operating distributed systems in production (e.g., Kubernetes, microservices, streaming systems)
• Experience improving systems for ML experimentation and evaluation
• Experience with big data or streaming technologies (e.g., Spark, Flink, or similar)
• Strong mathematical foundation (e.g., degree in Computer Science, Mathematics, Statistics, Physics, or related field)

• Experience with JVM languages (Java, Scala, or Kotlin)

Our interview process focuses on real-world experience building production ML models, and the ability to reason about the behaviors of realistic predictive systems. We support the use of AI tools in our development, but we want to understand your capabilities first. No AI tools will be allowed for remote interviews early in the process. The final interview will be in person and require travel (paid for by Mix Mode).

We are open to hiring great talent who may have qualifications above or below those specifically listed in this job description. Pursuant to California law, we must display the pay range for this job. Since we are willing to hire within a broad spectrum of qualifications, we also reflect a broad pay range. The base hourly range that we are targeting for this position is $160,000-$220,000 though we can adjust based on individual qualifications.

Individual salary is determined by qualifications, role, level, and location.

• Remote-First Work Culture
• Basic & Voluntary Life and AD&DD
• Flexible Spending Account (FSA)
• 401(k) with Employer Match
• Paid Holidays & Flexible Paid Time Off (PTO)

Mix Mode provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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