Applied ML Scientist — Security & Threat Analytics

SpyCloud; Austin (TX); Hybrid; USD 154,000 - 200,000; Full time

Benefits offered by this job

401(k) with Employer Contribution

Health, Vision, and Dental Insurance

Employer Paid Life Insurance

Generous PTO and holidays

Job summary

SpyCloud is seeking a Senior ML Engineer to design, train, and deploy production ML models for threat detection and risk scoring. You’ll own data validation, feature engineering, and end-to-end pipelines, collaborating with software and data engineers in AWS.

The role blends research and deployment, with NLP skills and hands-on experience in PyTorch, TensorFlow, scikit-learn, Airflow, Spark, and Pandas. We offer a competitive salary, remote-friendly options, and a solid benefits package.

Qualifications

• 4+ years of production ML experience with end-to-end data lifecycle ownership.
• Strong background in math (linear algebra, optimization, statistics) and ML.
• Experience with NLP for text classification, tagging, or entity extraction.
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn, XGBoost).
• Experience building/maintaining data pipelines (Airflow, Spark, Pandas) as part of modeling work.
• Experience in model versioning and monitoring in production (MLflow, DVC).
• Experience deploying models in cloud environments or containerized services.
• Strong communication skills.

Responsibilities

• Develop, train, and deploy ML models for threat detection and risk scoring.
• Own data validation, transformation, and pipeline health across research-to-production handoffs.
• Collaborate with software and data engineers to productionize models in AWS.
• Define success criteria with product managers and researchers; prototype MVPs.
• Document model decisions and participate in reviews and customer discussions.

Skills

Applied math

NLP

Python

ML libraries

Data pipelines

Model versioning

Cloud deployment

Tools

Airflow

Spark

Pandas

MLflow

DVC

Job description

SpyCloud is seeking a Senior ML Engineer to design, train, and deploy production ML models for threat detection and risk scoring. You’ll own data validation, feature engineering, and end-to-end pipelines, collaborating with software and data engineers in AWS.

The role blends research and deployment, with NLP skills and hands-on experience in PyTorch, TensorFlow, scikit-learn, Airflow, Spark, and Pandas. We offer a competitive salary, remote-friendly options, and a solid benefits package.