Staff AI Software Engineer

iManage • Toronto, ON

2d • Hybrid

About The Position

We offer a flexible working policy that supports a healthy balance between personal and professional well-being. This role requires in-office presence on Tuesdays & Fridays to collaborate, connect, and learn from peers - while also maintaining the flexibility for meaningful work-life balance. Being a Staff AI Software Engineer at iManage Means… You are passionate about owning the full lifecycle of AI systems, from training and fine-tuning models to deploying and scaling them in production. You thrive at the intersection of machine learning, data science, and infrastructure engineering, and you bring both analytical accuracy and hands-on technical depth to everything you build. You will work within the Applied AI team, collaborating with engineers, data scientists, and product stakeholders to build the AI capabilities that power iManage’s enterprise work platform including Ask iManage, our generative AI document assistant, as well as advanced document classification, extraction, and NLP-driven features that directly impact how knowledge workers search, organize, and understand their most critical information. You will tackle some of the most interesting problems in applying large language models and NLP at scale to enterprise documents and workflows. You are a self-starter who identifies problems before being asked, coordinates across teams, and drives solutions to completion. You think carefully about cost, performance, and reliability at scale as well as communicate with clarity and accountability at every step.

Requirements

• A Bachelor's, Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Statistics, or a related field
• The ability to work collaboratively across teams, communicate with precision, and take ownership from prototype to production
• 4+ years of experience in ML/AI engineering or software engineering with 3+ year of experience building and shipping in NLP and LLM systems into productions
• Deep proficiency in Python and modern AI frameworks (i.e., PyTorch and Hugging Face)
• Deep understanding of ML fundamentals including hands-on experience with both traditional ML/NLP and modern genAI/transformer architectures
• Demonstrated hands-on experience in fine-tuning language models and deploying them to production
• Experience with GPU optimization for both training and inference
• Experience with k8s deployment on cloud infrastructure (Azure/AWS/GCP) to optimize systems for scalability, latency, performance, operational complexity, and cost efficiency

Nice To Haves

• Experience in knowledge graph and multimodal LLMs
• Experience with distributed training (i.e, Pytorch distributed, Ray) and inference optimization framework (i.e, vLLM, SGLang)
• Experience with agentic engineering (agent harness, agent memory) and orchestration framework like LangChain/LlamaIndex, or similar tools

Responsibilities

• Owning the end-to-end ML lifecycle for AI systems from prototype to production, from model development and evaluation to scalable application design and production serving for NLP, genAI document intelligence, and agentic system use cases
• Collaborating with product and business stakeholders to translate requirements into viable technical solutions
• Deploying and optimizing ML/AI systems on GPUs and Kubernetes-based cloud infrastructure, including AKS or equivalent platforms, while balancing trade-offs across scalability, latency, performance, operational complexity, and cost efficiency.
• Applying modern engineering practices for production AI systems, including monitoring, observability, integration testing, containerized services, CI/CD pipelines, model/version tracking, and release governance.
• Driving architectural decisions for AI systems and mentoring team members to foster a culture of innovation and knowledge sharing

Benefits

• flexible working policy
• internal development framework
• unlimited access to LinkedIn Learning courses
• interactive Microsoft courses & training
• supportive and experienced team
• dynamic, inclusive, and encouraging culture
• flexible work hours
• modern, open-plan workspace
• gaming area
• free snacks and drinks
• regular social events
• inclusive environment
• market competitive salary
• annual performance-based bonus
• comprehensive Health/Vision/Dental/Life Insurance
• Registered Retirement Savings Plan with a company match up to 5%
• enhanced leave for expecting parents; 20 weeks 100% paid for primary leave, and 10 weeks 100% paid for secondary leave
• flexible time off policy
• multiple company wellness days each year
• access to RethinkCare, a global behavioral health platform

What This Job Offers

• Job Type: Full-time
• Career Level: Senior