Manager, MLOps Engineering$170,000-$190,000 + bonus + RSUs
Legal-tech
Toronto, Canada

About the Organization

Join a global company delivering intelligent information and technology solutions to professionals in legal, tax, compliance, and corporate sectors. The team is part of the organization's innovation hub, focused on applying AI, ML, and data science to create forward-looking tools.

The environment combines the best of both worlds: startup energy with enterprise support. Projects include building agentic systems to automate tax prep and document summarization for legal and financial workflows.

About the Role

This is a player/coach position, focusing on model deployment-ideal for someone with a strong foundation in software engineering and a passion for making machine learning work in the real world. You'll lead a team of MLOps engineers on experiments, iterate on PoCs, and help define how ML models are deployed, scaled, and maintained in production environments.

What You'll Bring

• 7+ years of software engineering experience in production environments
• 2+ years of team management experience working with ML systems (Python)
• Experience with ModelOps / MLOps workflows
• Background in:
• NLP: Named Entity Recognition / NER, information extraction, and information retrieval
• Numpy, Pandas, and scalable data handling
• Cloud environments (provider-agnostic)
• CI/CD pipelines, GitFlow, and Agile development
• Logging, alerting, testing, and autoscaling systems
• Strong collaboration and communication skills, including experience working with non-technical stakeholders
• Independent problem-solver with a proactive mindset

Preferred Experience

• Technical leadership on ML products
• Experience delivering LLM-based solutions
• Engineering management experience, including mentoring or leading cross-functional teams
• Familiarity with all stages of the AI product lifecycle
• Startup or fast-paced innovation environment experience
• People management of teams greater than 5

HOW TO APPLY

Please register your interest by sending your rsum to Tim Jonas via the Apply link on this page.

KEYWORDS

Machine Learning | GenAI | Gen AI | Generative AI | LLMs | Large Language Models | Artificial Intelligence | MLOps | Production | Machine Learning Operations | AI | Artificial Intelligence | Containerization | PyTorch | Python | Deployment | Deploying | MLFlow | Kubernetes | Kubeflow | ModelOps | NLP | Natural Language Processing | GitFlow | NER | Information Extraction | Information Retrieval