Machine Learning Engineer
Core
Building high-scale architecture and MLOps ecosystems to industrialize the ML lifecycle, ensuring models survive production at massive scale.
Role type
Senior Machine Learning Engineer (MLOps & Platform Engineering)
Builds
High-throughput distributed systems, resilient microservices, and automated data/model pipelines for AI-powered security products.
Domain
Cybersecurity / Human Risk Management / AI Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python (production-grade), PyTorch, Apache Spark, AWS (SageMaker, Lambda), Docker, Terraform/IaC, statistical analysis, inference optimization, CI/CD for ML, observability implementation, code review practices
Preferred skills
Feature Stores, automated feature engineering, custom inference optimization, MLflow, C#, JavaScript, secure coding practices
Technologies
Python, PyTorch, Apache Spark, AWS SageMaker, AWS Lambda, Docker, Terraform, MLflow
Responsibilities
Design and develop Machine Learning systems; transform data science prototypes into production-ready microservices; execute automated pipelines for data and model versioning; implement advanced monitoring for model drift and system health; optimize inference for low latency and high throughput; participate in rigorous code reviews.
Seniority
Senior, hands-on IC
