A fast-growing startup is to work with life sciences customers to support the deployment of AI-driven solutions in technical and operational environments.This is a cross-functional role that combines engineering, customer collaboration, data analysis, and technical problem-solving. You'll work with a range of stakeholders to understand operational challenges, analyze process and production data, develop models and workflows, and help drive improvements using the company's platform. If you are excited about being at the frontier of innovation in the application of AI, read on.Internally, you'll act as a technical subject matter expert and advocate for customer needs across manufacturing and process-related initiatives.Externally, you'll support enterprise customers by partnering with engineering and operations teams to maximize value from the platform, whether by improving existing workflows or helping implement recent solutions.In collaboration with Sales, Product, and Engineering, you'll also contribute to identifying new use cases and shaping future platform capabilities.ResponsibilitiesCustomer Engagement & Project DeliveryPartner with customers to support deployment and adoption of platform solutionsLead onboarding and implementation efforts across technical and operational environmentsBuild relationships with engineering, operations, and leadership stakeholdersIdentify opportunities for operational improvement and data-driven insightsTranslate customer challenges into actionable technical solutions and product feedbackSupport projects from discovery through implementation and impact measurementTechnical Analysis & Problem SolvingAnalyze operational and process datasets to identify trends, bottlenecks,



and optimization opportunitiesDevelop analytical models, simulations, and workflows using Python and related toolsWork with industrial data systems and manufacturing datasetsCollaborate with product and engineering teams to improve platform functionalityCommunicate technical findings to both technical and non-technical audiencesSupport troubleshooting and continuous improvement initiatives in complex operational settingsQualifications7-10 years of experience in manufacturing, process engineering, or related industrial environments, with strong understanding of biologics pharma manufacturingExperience building models from scratch, not just black-box developmentExperience in dynamic modelling, hybrid modelling is essential to be successfulUnderstanding of production, pilot, or laboratory-scale operationsRequired SkillsExperience using Python or similar tools for analysis, modelling, or automationAbility to work with operational and process dataStrong communication and stakeholder management skillsProblem-solving mindset with experience driving technical or operational improvementsExperience working in cross-functional technical teamsExperience with Aspen, Python or related modelling tools for mechanistic modellingExperience in pharmaceutical manufacturing execution systems (MES)Experience such as the below in highly relevant to the positionBioprocess scale-up; Cell Culture ModelingCell culture modelingCHO cell modelingBioreactor modelingFermentation modelingBioprocess modelingUpstream process modelingMetabolic modelingMetabolic flux analysis (MFA)Flux balance analysis (FBA)Genome-scale metabolic models (GEMs)Media optimization modelingNutrient consumption modelingProduct quality modelingCell growth kineticsMechanistic process understanding #J-18808-Ljbffr

📌 Principal Product Engineer, Pharma Or Chemical Manufacturing (Toronto)
🏢 Optimyze1
📍 Toronto