Senior MLOps Engineer

DeepRec.ai; Toronto; Remote; CAD 120,000 - 160,000; Full time

Job summary

An innovative AI company is seeking a talented MLOps Engineer to develop and maintain robust machine learning pipelines for real-time AI and video applications. This role involves collaborating with AI researchers and data scientists to deploy state-of-the-art models, optimize real-time inference, and ensure scalable systems. If you're passionate about automation and clean system design, this opportunity offers a dynamic work environment where your contributions will shape the future of media technology. Join a team of experts and make a significant impact in the rapidly evolving AI landscape.

Qualifications

• 3+ years of experience in MLOps, DevOps, or AI model deployment.
• Strong skills in Python and frameworks like TensorFlow and PyTorch.

Responsibilities

• Design and optimize ML pipelines for training, validation, and inference.
• Automate deployment of deep learning and generative models for real-time use.

Skills

MLOps

Python

TensorFlow

PyTorch

Docker

Kubernetes

CI/CD

Distributed Systems

Education

Bachelor’s in Computer Science

Master’s in Computer Science

Tools

AWS

GCP

Azure

ArgoWorkflow

Kubeflow

MLflow

Airflow

Job description

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This range is provided by DeepRec.ai. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

CA$120,000.00/yr - CA$160,000.00/yr

Direct message the job poster from DeepRec.ai

Co-Founder and Managing Director USA @ DeepRec.ai #MachineLearning #Staffing #Hiring #DeepLearning #DeepTech #AppliedResearch #NLP #LLM #GenAI #MLOps

Senior MLOps Engineer – Real-Time AI & Video Applications (100% Remote)

Job Type: Full-time

We're hiring for an innovative AI company focused on real-time AI and Video Applications. Their team comprises leading experts in computer graphics and generative modeling, experiencing rapid growth. We're seeking experienced MLOps Engineers eager to work on cutting-edge real-time AI applications shaping the media landscape.

The Role

We’re looking for a talented MLOps Engineer to develop and maintain robust machine learning pipelines and infrastructure. You’ll collaborate with AI researchers, data scientists, and software engineers to deploy state-of-the-art models into production, optimize real-time inference, and ensure scalable systems.

What You’ll Do

• Design and optimize ML pipelines for training, validation, and inference
• Automate deployment of deep learning and generative models for real-time use
• Implement versioning, reproducibility, and rollback capabilities
• Deploy and manage containerized ML solutions on cloud platforms (AWS, GCP, Azure)
• Optimize model performance using TensorRT, ONNX Runtime, and PyTorch
• Work with GPUs, distributed computing, and parallel processing to power AI workloads
• Build and maintain CI/CD pipelines using tools like GitHub Actions, Jenkins, ArgoCD
• Automate model retraining, monitoring, and performance tracking
• Ensure compliance with privacy, security, and AI ethics standards

What You Bring

• 3+ years of experience in MLOps, DevOps, or AI model deployment
• Strong skills in Python and frameworks like TensorFlow, PyTorch, ONNX
• Proficiency with Docker, Kubernetes, and serverless architectures
• Hands-on experience with ML tools (ArgoWorkflow, Kubeflow, MLflow, Airflow)
• Experience deploying and optimizing GPU-based inference (CUDA, TensorRT, DeepStream)
• Solid grasp of CI/CD practices and scalable ML infrastructure
• Passion for automation and clean, maintainable system design
• Strong understanding of distributed systems
• Bachelor’s or Master’s in Computer Science or equivalent work experience

Bonus Skills

• Experience with CUDA programming
• Exposure to LLMs and generative AI in production
• Familiarity with distributed computing (Ray, Horovod, Spark)
• Basic networking knowledge

Please apply now for more details and next steps.

We look forward to hearing from you.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Technology, Information and Media, Information Services, and Consumer Services