Availability awaiting confirmation
We are waiting for a fresh update from the source. This page preserves the last received job details; current availability is not confirmed.
Job description
Overview
Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design, develop, and deploy state-of-the-art computer vision and language models that power scalable, real-world solutions. You’ll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.
As part of our AI team, you’ll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands‑on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.
Responsibilities
Fine‑tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
Develop vision‑language models and Mixture of Experts architectures, from experimental design through production deployment.
Architect Retrieval‑Augmented Generation (RAG ) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
Contribute to our machine learning repositories and optimize models for performance, scalability, and real‑time inference across edge and cloud environments.
Drive performance optimization and scalability of ML systems across edge and cloud environments.
Collaborate with cross‑functional teams to integrate computer vision solutions into end‑to‑end products, translating research outcomes into measurable platform impact.
This list of responsibilities might not cover everything you'll end up doing.
Qualifications
5+ years of hands‑on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
Experience building and deploying LLM-based systems and Retrieval‑Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.
#J-18808-Ljbffr
Worksite address
frisco, TX, 75034, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.