AI/ML Ops Engineer: Build Production ML Pipelines

Socket.dev; New York (NY); Remote; CAD 120,000 - 170,000; Full time

Benefits offered by this job

Health, Vision, Dental, Life Insurance

401k plan and discretionary time off

Equity participation

Job summary

Blackpoint Cyber is seeking an AI/ML Ops Engineer to own the operational backbone of our AI/ML capability, taking models from training through production deployment and ensuring a scalable, reliable AI lifecycle. You will stand up deployment pipelines, put trained scripts on endpoints, and ensure production-grade monitoring and alerting.

You will report to the VP of AI and Data and collaborate with Engineering, SOC, and APG to advance our AI architecture and governance utilities while building

Qualifications

• 5+ years of hands-on ML Engineering experience with production deployments.
• Ability to own deployment pipelines end-to-end, from training to live endpoints.
• Strong analytical and data-driven decision-making abilities.
• Excellent communication and collaboration with stakeholders at all levels.

Responsibilities

• Own the AI/ML loop end-to-end across all pipelines, from training to deployment and retirement.
• Develop, optimize, and deploy ML models with hands-on experience.
• Design and administer model-building and serving infrastructure for real-time requests.
• Implement containerized Infrastructure as Code (Terraform, GitHub Actions, Docker, Kubernetes).
• Build standardized container pipelines for training, feature engineering, and inference channels with CI/CD.
• Lead test strategy across the ML pipeline and ensure production-grade visibility and alerting.

Skills

ML Engineering

End-to-end deployment

Analytical thinking

Communication skills

Tools

AWS

SageMaker

Bedrock

Kafka

Spark

MLFlow

Sagemaker Pipelines

Terraform

GitHub Actions

Docker

Kubernetes

ECS/EKS

Python

Bash

SQL

SparkSQL

GitFlow

CI/CD

DevOps

Grafana

CloudWatch

Job description

Blackpoint Cyber is seeking an AI/ML Ops Engineer to own the operational backbone of our AI/ML capability, taking models from training through production deployment and ensuring a scalable, reliable AI lifecycle. You will stand up deployment pipelines, put trained scripts on endpoints, and ensure production-grade monitoring and alerting.

You will report to the VP of AI and Data and collaborate with Engineering, SOC, and APG to advance our AI architecture and governance utilities while building