Machine Learning Engineer

2 weeks ago


Canada Quantix Search Full time

Machine Learning Engineer (MLOps/Tooling)

Remote (Preference for Canada based)

CA $90k - CA$160k (DOE) + Equity

About the Client:

Our client is at the forefront of revolutionizing a critical industry using cutting-edge AI and machine learning technologies. They're on a mission to transform how organizations make data-driven decisions, empowering them to tackle some of the toughest challenges with high-impact solutions. Backed by top investors, the company is scaling rapidly, and their AI solutions are already making waves across the industry.

About the Role:

As a Machine Learning Engineer (MLOps/Tooling), you'll be responsible for building and scaling the robust infrastructure that powers our client's groundbreaking AI models. Your work will directly impact the deployment, monitoring, and optimization of AI systems, ensuring they are reliable, scalable, and efficient. If you're ready to tackle challenges at the intersection of machine learning and infrastructure, this is the role for you

Key Responsibilities:

  • Build and maintain scalable MLOps pipelines to deploy and monitor models seamlessly.
  • Create and optimize data processing tools that integrate with multiple systems for maximum efficiency.
  • Convert prototypes into high-performance, production-grade Python code.
  • Collaborate with cross-functional teams to solve complex challenges and continuously improve the AI infrastructure.

What We're Looking For:

  • We're open to a range of experience starting right from new grads, but must have Applied ML experience either through recent roles or internships.
  • Experience in machine learning and MLOps.
  • Proficiency in Python, Pytorch, cloud platforms (AWS, GCP, or Azure), and containerization (Docker/Kubernetes).
  • Hands-on experience with MLOps tools like MLflow, DVC, and building scalable data pipelines.
  • A collaborative, problem-solving mindset with a passion for innovation and AI.

If you're excited about building scalable AI systems and want to be part of a team that's reshaping an entire industry, apply today



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