Machine Learning Engineer

About Halo Media

Halo Media is a digital innovation agency and precision engineering partner. For over 20 years, we’ve blended visionary design with technical depth to build scalable digital products for global brands and high-growth startups. With an AI-forward mindset and a focus on measurable outcomes, we help our clients move faster and smarter—turning complex business challenges into high-performance solutions.

Role Overview

We are seeking hands-on Machine Learning Engineers for an urgent staff augmentation engagement (6-month temporary role, with a possibility of extension). In this role, you will support, fix, and optimize a high-traffic, global consumer platform. Operating under the direct guidance of a Staff ML Architect, you will focus heavily on daily MLOps execution, pipeline maintenance, and ensuring models perform reliably in a production-grade environment.

Key Responsibilities

• Model Lifecycle Management: Design, deploy, and monitor machine learning models within high-traffic environments, ensuring maximum reliability, performance, and scalability.

• Pipeline Execution: Maintain, troubleshoot, and optimize end-to-end ML pipelines. Integrate tools like Spark and Airflow to streamline the flow from raw data ingestion through to offline and online model evaluation.

• Daily MLOps: Execute daily model training and inference tasks. Build and manage automated containerized deployments to ensure smooth, continuous support for a major production platform.

Required Qualifications

• Experience: 1–3 years of hands-on experience in Machine Learning, MLOps, or Data Science within a professional environment.

• GCP Expertise: Solid experience with the Google Cloud Platform ecosystem, particularly Vertex AI components (Workbench, Pipelines, Model Registry).

• ML Frameworks & DevOps: Proficiency in modern ML frameworks (e.g., PyTorch) and containerization tools (Docker) for automated builds.

• Data Orchestration: Practical experience managing data processing flows using Apache Spark and Airflow.

Preferred Skills

• Familiarity with real-time model serving and infrastructure (e.g., Triton Inference Server, Terraform).

• Previous experience in high-traffic, production-grade environments.

Position Type: 6 month temporary employee

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

Salary Range: $55-$60/hr