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This listing was closed on Jul 19, 2026.
Browse Open JobsPrincipal Machine Learning Engineer, General AI, ML & Big Data
Summary by AIEngineer.careers
Principal Machine Learning Engineer, General AI, ML & Big Data is a AI Engineer role (full-time). with C-Serv. in MONTRÉAL, CA. Imported listing (source: ziprecruiter.com). Apply on the employer's site (ziprecruiter.com).
Imported listing (source: ziprecruiter.com) · Apply on ziprecruiter.com
MONTRÉAL · CA
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Full-time
PRINCIPAL
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from ziprecruiter.com
This Principal Machine Learning Engineer role focuses on building intelligent multi-agent systems for a global networking leader. You will shape ML strategy, design high-performance microservices, and deploy real-time inference pipelines. The position involves mentoring engineers and driving technical vision across Generative AI, AI Agents, RAG, and LLM fine-tuning projects.
Responsibilities
- Define and drive technical vision for ML solutions across products and platforms.
- Own end-to-end software development lifecycle from design to deployment.
- Architect high-performance scalable microservices including sync/async web services.
- Build real-time inference pipelines using Triton, TensorRT, and mixed-precision computing.
- Mentor engineers and foster strong team culture.
- Champion engineering excellence and continuous improvement.
Requirements
- Degree in Computer Science, Mathematics, or related field.
- 5–10 years of full software development lifecycle experience.
- 5–10 years of Python expertise.
- Strong experience designing RESTful APIs (e.g., FastAPI).
- Proficiency with Docker, Kubernetes, and CI/CD pipelines.
- 3+ years designing large-scale distributed systems on cloud platforms (AWS, Azure, or GCP).
C-Serv
Round Rock · US · 50+ employees
C-Serv is a professional services firm that specializes in deployed workforce solutions and managed IT consulting. They help high-growth organizations scale by providing vetted technology teams and operational expertise.
