Senior ML Engineer (MLOps & Backend / Ops)

AutoAlign AI; Toronto; Hybrid; CAD 90,000 - 130,000; Full time

Job summary

A technology firm in Toronto is seeking a Senior Machine Learning Engineer to design and implement ML systems and manage backend services. The ideal candidate will have over 5 years of experience in MLOps and backend development, strong Python proficiency, and the ability to work with cloud platforms like GCP and AWS. This role offers competitive compensation and a flexible work environment.

Benefits

Competitive compensation and benefits package

Flexible hybrid/remote work setup

Opportunity to influence across ML systems

Qualifications

• 5+ years of professional experience in ML engineering, MLOps, and backend/operations roles.
• Strong proficiency in Python and ML frameworks.
• Proven experience developing and operating backend APIs.

Responsibilities

• Design, implement, and optimize scalable ML pipelines.
• Deploy and maintain models on cloud platforms.
• Build and manage CI/CD pipelines for ML workflows.

Skills

MLOps

Python (FastAPI, Flask, Django)

ML frameworks (PyTorch, TensorFlow, Scikit-learn)

Backend API Development

Cloud Platforms (GCP, AWS, Azure)

CI / CD Pipelines

Kubernetes

Docker

Terraform

Data Pipelines (ETL/ELT)

Tools

GCP Vertex AI

AWS Sagemaker

Azure ML

Kubernetes clusters

Job description

About AutoAlign AI

Type : Full-time, Permanent

About AutoAlign AI: At AutoAlign AI, we build trustworthy, industrial-focused agentic AI assistants that help manufacturers, insurers, and field-service providers deliver with higher accuracy and efficiency.

Our AI-powered supervisor platform enables advanced quality control and operational intelligence across manufacturing and automotive workflows. By supporting SOP validation and building industry-specific AI agents, we empower front-line workers to perform their jobs more efficiently while ensuring accuracy, efficiency, and safety.

We partner with global leaders such as NVIDIA, KPMG, BASF to deliver cutting-edge solutions that scale securely in enterprise environments. Based in Toronto, we are growing fast and looking for passionate engineers to join us on this journey.

About the Role

We are looking for a Senior Machine Learning Engineer with expertise in MLOps, backend development, and broader operational infrastructure to design, build, and scale reliable ML and software systems. In addition to productionizing ML models, you’ll play a key role in managing general Ops responsibilities—including backend API and services, cloud infrastructure, and system performance—for our AI-driven web, mobile, and wearable AI such as smart glass applications.

This senior-level role combines hands-on engineering with technical leadership, making you a bridge between data science, backend engineering, and DevOps / Cloud operations.

Key Responsibilities

• Design, implement, and optimize scalable ML pipelines covering training, evaluation, inference, and monitoring in modern cloud environments.
• Deploy and maintain models and artifacts in production on cloud platforms (GCP, AWS, Azure) using containerized environments (Docker, Kubernetes).
• Build and manage CI / CD pipelines for ML workflows, backend services, and general applications.
• Manage and optimize GPU infrastructure as well as general compute / storage infrastructure, balancing cost, scalability, and reliability. By defining best practices in infrastructure-as-code.

Server-Side Development and Leadership

• Develop and maintain backend services and scalable, secure, and low-latency APIs that connect ML models to web and mobile AI applications.
• Work with the frontend team to integrate AI features into React Native, web, and AR / VR applications.
• Participate in requirement discovery sessions with clients and own technical architectural parts of the client project and deliveries
• Implement mission-critical backend features by understanding client requirements and collaborating with data scientists and front-end developers

Required Skills & Qualifications

• 5+ years of professional experience in ML engineering, MLOps, and backend / operations roles.
• Strong proficiency in Python (FastAPI, Flask, Django) and ML frameworks (PyTorch, TensorFlow, Scikit-learn, Generative AI libraries).
• Proven experience developing and operating backend APIs for web or mobile applications.
• Hands-on experience with cloud platforms (e.g., GCP Vertex AI, AWS Sagemaker, Azure ML, Kubernetes clusters).
• Strong knowledge of CI / CD pipelines, Kubernetes, Docker, Terraform, Helm, GitOps.
• Understanding of data pipelines (ETL / ELT, batch & live video, audio, text streaming).
• Excellent communication and problem-solving skills, with the ability to work cross-functionally.

What We Offer

• Competitive compensation and benefits package.
• Flexible hybrid / remote work setup within Ontario.
• Opportunity to shape end-to-end infrastructure—from ML to backend to Ops—powering real-world AI applications.
• A collaborative, growth-oriented environment where you’ll have ownership and influence across ML systems and operational infrastructure

Please send your resume and cover letter to [e-mail]

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Technology, Information and Internet

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