Blackpoint Cyber is looking for a Senior Machine Learning Engineer to operate as a technical lead for the machine learning function within our A.I. business unit. You will build out our machine learning solutions to support the development of A.I. products and features, reporting directly to the Head of Artificial Intelligence.

What You'll Do

Develop, optimize, and deploy ML models.
Design, build, and administrate model building and serving infrastructure.
Implement ML workflows as containerized Infrastructure as Code.
Build and automate standardized container pipelines for training, feature engineering, and inference channels.
Conduct performance, load, and deployment testing of delivered ML solutions.
Develop ML governance utilities for oversight and administration of deployed infrastructure.
Implement data, feature, and model lifecycle best practices.
Contribute to A.I. architecture and design decisions.
Collaborate closely with cross-functional teams, including Engineering, our Security Operations Center (SOC), and our Adversary Pursuit Group (APG).

What We're Looking For

5+ years of hands-on ML Engineering experience, with a track record of delivering A.I. products and services into production.
Experience building with a well-architected mindset for efficiency, performance, security, and reliability.
Strong analytical and problem-solving abilities, with a focus on data-driven decision-making.
Excellent communication and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels.
Cloud-based ML Infrastructure (AWS).
Model Development & Deployment Operations (SageMaker, Airflow).
Inference Streams & Event-driven Processing (Kafka, Spark).
MLOps Workflows (Airflow, MLFlow, KubeFlow).
Pipeline Automation (A.I. CI/CD, Infrastructure as Code).
ML Governance (Data, Model, & Feature Versioning, Monitoring & Testing).
Containerized Services (Docker, Kubernetes).
Scripting Language (Python, Bash).
Query Language (SQL, Ksql).
GitFlow & DevOps Best Practices.