3 months ago
Toronto, CanadaSenior
Responsibilities
- Own the end-to-end ML lifecycle from model development and evaluation to scalable production serving.
- Develop generative AI document intelligence, LLM-driven features, and agentic systems.
- Deploy and optimize AI systems on GPUs and Kubernetes-based cloud infrastructure such as AKS.
- Design and implement production-ready LLM applications and APIs with monitoring, observability, and integration testing.
- Build containerized services and apply CI/CD, model and version tracking, and release governance practices.
- Optimize systems for scalability, latency, performance, operational complexity, and cost efficiency.
- Collaborate with product and business stakeholders to translate requirements into technical solutions.
- Conduct code reviews and provide constructive feedback to team members.
- Contribute to AI engineering best practices and standards across the team.
Requirements
- Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Statistics, or a related field.
- At least 3 years of experience in ML/AI engineering or software engineering.
- Hands-on experience building and shipping LLM systems into production.
- Deep proficiency in Python, PyTorch, and Hugging Face.
- Understanding of traditional machine learning, generative AI, and transformer architectures.
- Demonstrated experience fine-tuning language models and deploying them to production.
- Experience optimizing GPUs for training and inference workloads.
- Experience deploying Kubernetes workloads on Azure, AWS, or GCP cloud infrastructure.
- Preferred experience with PyTorch Distributed, Ray, vLLM, SGLang, LangChain, LlamaIndex, agent harnesses, agent memory, knowledge graphs, multimodal LLMs, AI/ML observability tools, and model lifecycle management.
- Ability to collaborate across teams, communicate precisely, and take ownership from prototype through production.
Benefits
- Flexible hybrid work policy with in-office collaboration required on Tuesdays and Fridays.
- Flexible work hours and a modern open-plan workspace with a gaming area, free snacks and drinks, and regular social events.
- Internal career development framework and unlimited access to LinkedIn Learning and Microsoft courses and training.
- Comprehensive health, vision, dental, and life insurance.
- Registered Retirement Savings Plan with company matching up to 5%.
- Enhanced parental leave including 20 weeks of fully paid primary leave and 10 weeks of fully paid secondary leave.
- Flexible time off policy and multiple company wellness days each year.
- Access to RethinkCare behavioral health and well-being resources.
- Annual performance-based bonus.
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