We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Staff Applied AI/ ML Engineer at Gusto, Inc.. Location Information: Canada. About the role. Gusto’s AI/ML Eng team leverages our rich dataset to guide product direction and decision-making by building the right solutions at scale. We’re looking for a senior technical leader (individual contributor) who will design robust AI/ML systems and services through close partnership with seasoned leaders across Engineering, Product, Design, Data Science, Marketing, and Customer Excellence. This means you will also define the strategy along with shipping impactful models and services to evolve our AI/ML capabilities and practices.. We have several open roles across two embedded areas:. Unified Service Platform optimizes our customer experience, creates personalized engagement moments, and drives automated or AI enhanced assistance. We develop AI tools and platform components (ex. embedding algorithms) to improve performance and customer satisfaction.. Growth builds AI/ML-powered experiences that drive relevant, timely product adoption. Our team enables contextual customer interactions through growth-oriented capabilities like propensity modeling and recommendations.. Here’s what you’ll do day-to-day. Design and develop scalable, production-grade AI/ML models and services for complex business and customer experience problems.. Lead technical strategy and architecture for key AI/ML domains, including model lifecycle, observability, safety, and evaluation.. Collaborate cross-functionally to identify high-leverage AI/ML opportunities, translate them into actionable roadmaps, and deliver measurable outcomes.. Build, harden, and operate platform capabilities that power customer journey experiences (e.g., personalization, assistance, routing, content selection).. Stay current with the latest AI/ML research; prototype, evaluate, and productionize new algorithms and techniques from academia and industry.. Establish robust practices for validation, deployment, monitoring, explainability, and ongoing performance management.. Communicate findings, roadmaps, tradeoffs, and impact clearly to executives and non-technical partners.. Mentor engineers and scientists, fostering a culture of technical excellence and pragmatic innovation.. Here’s what we’re looking for. 8+ years of hands-on experience building and deploying end-to-end AI/ML systems in industry or academia.. Deep expertise in one or more advanced ML areas (e.g., supervised/unsupervised learning, deep learning, NLP, LLMs, retrieval/RAG, reinforcement learning). . Our Growth positions would require a background in growth-oriented solutions (e.g., propensity scoring, recommendation systems, forecasting, lead scoring) and experimentation.. Proven track record delivering large, impactful AI/ML projects into production environments with measurable business and customer impact. . Experience monitoring AI agents with an attention to safety/guardrails, evaluation frameworks, and sentiment/quality analysis is necessary for the Unified Service Platform roles but not required for our Growth positions.. Proficiency with modern ML frameworks and tooling (e.g., PyTorch, TensorFlow, Hugging Face) and cloud platforms (e.g., GCP, AWS, or Azure). . Hands-on experience building LLM-based applications and agentic AI workflows (e.g., Claude, Gemini, OpenAI), including prompt/retrieval design and evaluation, is a bonus.. Strong programming skills in Python and sound software engineering fundamentals (testing, code review, CI/CD, reliability).. Demonstrated leadership in cross-disciplinary settings and the ability to influence direction through technical depth and clarity.. Excellent communication skills and strong product/business judgment.. Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field is a plus.. Our cash compensation amount for this role is targeted at $230k-280k for San Francisco, New York, and Seattle $205k - 255k in Los Angeles, $185k-234k in Denver, and 200k-250k CAD for Toronto. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.