Senior Machine Learning Operations Engineer II (AI)

TL;DR

Senior Machine Learning Operations Engineer II (AI): Designing and scaling infrastructure and automated pipelines to reliably train, deploy, and monitor ML models in production with an accent on CI/CD, distributed infrastructure, and system reliability. Focus on automating Continuous Training (CT) pipelines, optimizing GPU/CPU clusters, and implementing robust observability for data and concept drift.

Location: Remote (Must be based in the US or Canada)

Salary: $148,000 – $216,000 USD (US) / $171,500 – $201,000 CAD (Canada)

Company

hirify.global provides location sharing and safety services for families, serving nearly 100 million monthly active users globally.

What you will do

• Design and manage automated CI/CD and Continuous Training (CT) pipelines for ML model development and delivery.
• Containerize and scale ML models as high-availability microservices or batch processing workflows.
• Establish unified logging, alerting, and monitoring to track model performance, latency, and data drift.
• Provision and optimize cloud-based ML infrastructure using Infrastructure as Code (IaC) paradigms.
• Collaborate with product teams to drive infrastructure adoption via SDK/API development and system maintenance.
• Implement robust lineage tracking for data, code, and model artifacts to ensure compliance and reproducibility.

Requirements

• 5+ years of professional software engineering, DevOps, or data engineering experience.
• 2+ years specifically dedicated to building and maintaining MLOps infrastructure.
• Strong proficiency in Python and software engineering best practices (unit testing, modular design).
• Hands-on experience with Docker and Kubernetes (EKS, GKE).
• Familiarity with ML lifecycle tools: MLflow, Kubeflow, SparkML, and Airflow.
• Practical experience with major cloud ecosystems (AWS, GCP, or Databricks).

Nice to have

• Experience implementing production feature stores (e.g., Feast, Tecton) and model registries.
• Experience deploying and optimizing LLMs using frameworks like vLLM, Triton, or TGI.
• Proficiency with Terraform for managing reproducible environments.
• Familiarity with distributed computation engines such as Apache Spark, Ray, or Dask.
• Relevant cloud or architecture certifications (e.g., AWS ML Specialty, CKA).

Culture & Benefits

• Remote-first work environment with equipment and tool reimbursement.
• Comprehensive medical, dental, and vision insurance (100% paid for US employees).
• 401(k) matching (US) and RRSP with DPSP (Canada).
• Flexible PTO and 12 company-wide days off per year.
• Learning and Development programs to support professional growth.
• Free hirify.global Platinum Membership for the employee's circle.