• Design, develop, and deploy AI/ML solutions to modernize core pharmacy platforms, with a focus on scalability, reliability, performance, and security • Leverage Generative AI, LLMs, and agentic AI frameworks to automate and enhance pharmacy workflows and decision-making processes • Collaborate with business and technical stakeholders to understand pharmacy domain requirements and translate them into robust AI/ML-driven technical solutions • Contribute to architecture and technical design of AI/ML pipelines, including model selection, data integration, and deployment patterns • Establish and maintain AI/ML engineering standards, best practices, and quality assurance processes • Conduct code reviews, provide constructive feedback, and mentor engineers on modern AI/ML engineering practices • Partner with cross-functional teams including data scientists, product managers, platform engineers, and pharmacy domain experts • Translate legacy system modernization needs into scalable AI applications that enhance products, workflows, and operational efficiency • Monitor and optimize AI/ML model performance, resource utilization, and platform reliability • Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and operations of AI/ML solutions • Stay current with advancements in AI/ML frameworks, Generative AI, LLMs, and pharmacy technology modernization

• Support balancing and simulation work across core game systems: heroes, troops, economy, progression, and events • Help improve and operate our AI-assisted balancing toolchain and workflows • Build scripts, automations, and ML-supported workflows to improve balancing efficiency and iteration speed • Analyze balancing data, simulation outputs, and player behavior signals to support balancing decisions • Work closely with game design, QA, engineering, and production on balancing topics and tooling improvements • Help document and structure balancing processes, prompts, datasets, and workflows for scalable AI-assisted production

• Build and maintain large-scale distributed training and evaluation pipelines for Deep Reinforcement Learning. • Design scalable infrastructure for training, evaluation, model management, and experiment tracking. • Build dashboards and monitoring tools to track training progress, model quality, compute usage, and agent performance. • Optimize the training and inference performance of our Deep Learning models. • Improve cost efficiency across cloud/GPU infrastructure and make high-impact infrastructure decisions. • Work closely with researchers and engineers to reduce iteration time and improve model accuracy. • Help design reproducible ML workflows, including data pipelines, checkpointing, evaluation, versioning, and deployment. • Identify bottlenecks across the full ML stack: model architecture, data loading, GPU utilization, distributed training, inference, and infrastructure. • Contribute directly to ML improvements that increase accuracy, robustness, and compute efficiency.

Role Description We are looking for engineers with passion for using machine learning to create intelligent applications. As a Machine Learning Engineer, you will be part of the Data Science team inside the Product and Tech group with +2200 brilliant developers, engineers, analysts and researchers. You will collaboratively design, build, and productionize machine learning systems. As a member of the logistics data science team, you will develop solutions to supply and demand challenges while optimizing logistics algorithms to ensure a reliable, efficient, and profitable service. From predicting ETAs to solving pricing problems, our ML pipelines form the backbone of our delivery operations. Location: Remote Canada Reporting to: Technology Manager, Machine Learning - Proven academic/industry experience in Machine Learning or similar, developing technologies for forecast or logistics products. - Strong coding and software engineering skills in a mainstream programming language; Python preferred. - Able to work independently and solve complex problems, with a demonstrated ability to productize and deploy using cloud services (eg. Amazon Web Services, Google Cloud Platform). - Strong background in working with microservices and event-driven architecture, serverless computing, and cloud architecture patterns. - Familiarity with ML tools and packages like TensorFlow, pyTorch etc. - Practical experience building and optimizing production quality machine learning applications making use of engineering best practices, automation and experimentation. - Understanding of machine learning algorithms and ability to apply them in data driven processing systems. - Ability to quickly prototype ideas/solutions, perform critical analysis, and use creative approaches for solving complex problems. - Ability to collaborate closely with multi-functional teams, driving forward best practices. - Clear oral and written communication. Qualifications - Researching, implementing, and deploying innovative ML techniques applicable to logistics problems. - Scaling and transferring novel machine learning solutions to improve our decision making processes and solutions in their different product use cases. - Implementing and launching Data Science applications that coordinate with front facing solutions; constant improvements using performant and efficient ML models. - Implementing tools, data pipelines, and evaluation frameworks to enable development, iteration, and launch of ML ideas within the product scope. Benefits - Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment. - Fun, fast-paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers. - Inclusion, Diversity & Belonging: We’re committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day. Company Description Want to know more about our JETers, culture or company? Have a look at our career site where you can find people's stories, blogs, podcasts and more JET morsels.