Software Product Owner, AI

When joining PerkinElmer, you select an experienced and trusted leader in scientific solutions, with the support of a global service network and distribution centers, providing the right solution, at the right time, to meet critical customer needs.  With over an 80+ year legacy of advancing science and a mission of innovating for a healthier world, our dedicated team collaborates closely with commercial, government, academic and healthcare customers to deliver our broad portfolio of analytical solutions, and OneSource services.

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Job Title: Software AI Product Owner (Analytical Instruments) 

About Us: 
PerkinElmer is a global leader providing analytical solutions and services focused on the applied, food, and enterprise services markets.  

Job Summary: 
We are seeking a highly motivated and experienced AI Product Owner (AI PO) to lead the development and maximize the value of cutting-edge AI/ML solutions integrated with our analytical instruments. You will be the crucial link between business stakeholders, domain experts (scientists/engineers), data science teams, and engineering teams (software, firmware, hardware). Your primary goal is to translate complex instrument data and user needs into actionable AI product features that deliver real-time insights, automation, and enhanced capabilities directly at the point of data generation or on a cloud. 

Key Responsibilities: 

Product Vision & Strategy: Define, articulate, and champion the product vision and roadmap for AI capabilities embedded within or connected to our analytical instruments. 

Backlog Management: Create, maintain, and prioritize the product backlog, translating high-level requirements and scientific/user needs into detailed user stories, acceptance criteria, and AI/ML model performance targets suitable for edge deployment. 

Stakeholder Collaboration: Act as the primary point of contact between business units, instrument R&D, data scientists, ML engineers, software/firmware engineers, and end-users. Effectively communicate strategy, progress, and technical considerations. 

AI/ML Requirements Definition: Elicit and define requirements for AI/ML models, considering the unique characteristics of data generated by analytical instruments (e.g., spectra, chromatograms, images, sensor time-series) and the constraints of edge environments (compute, memory, power, connectivity). 

Data Strategy & Acumen: Collaborate on defining data acquisition strategies, data quality requirements, annotation/labeling needs, and validation approaches specific to instrument data. Understand and mitigate potential biases in sensor data. 

Deployment Focus: Guide the product development process with a deep understanding of deployment environment constraints. Prioritize features and model complexities appropriate for on-device or cloud inference, considering latency, throughput, security, and model update strategies. 

Value & Success Definition: Define clear success metrics for AI features, often involving probabilistic measures (accuracy, precision, recall) tailored to the specific analytical task and acceptable performance thresholds on edge hardware. Focus relentlessly on the business and scientific value delivered. 

Experimentation & Iteration: Facilitate the iterative and experimental nature of AI development. Guide hypothesis testing, interpret model results, and make data-driven decisions to pivot or persevere. 

Responsible AI & Ethics: Champion responsible AI practices, ensuring fairness, transparency, explainability (where feasible), and ethical considerations are addressed throughout the product lifecycle, particularly concerning data privacy and model behavior on distributed devices. 

Cross-Functional Leadership: Lead agile ceremonies (sprint planning, reviews, retrospectives) and foster strong collaboration within cross-functional teams to deliver end-to-end AI solutions, from data ingestion and model training to edge deployment and monitoring. 

Required Qualifications: 

• Bachelor's degree in Computer Science, Engineering, Data Science, Physics, Chemistry, or a related technical field. 

• Proven experience (3+ years) as a Product Owner, Product Manager, or Business Analyst in an Agile software development environment. 

• Demonstrable understanding of core AI/ML concepts, workflows, and common techniques. 

• Experience working with technical products, ideally involving hardware, IoT devices, sensor data, or embedded systems. 

• Strong understanding of the product development lifecycle, from ideation to launch and iteration. 

• Excellent communication, negotiation, and stakeholder management skills – ability to translate between technical and non-technical audiences. 

• Experience defining requirements and acceptance criteria for complex systems. 

• Data-driven decision-making mindset. 

Preferred Qualifications: 

• Master's or PhD in a relevant technical field. 

• Direct experience as a Product Owner for AI/ML-powered products. 

• Experience specifically with edge computing, AI on edge devices (e.g., TensorFlow Lite, ONNX Runtime, NVIDIA Jetson, etc.), or MLOps. 

• Familiarity with analytical instrumentation (e.g., spectroscopy, chromatography, microscopy, spectrometry) or scientific data analysis. 

• Experience working in regulated environments (if applicable, e.g., Life Sciences, Industrial). 

• Understanding of hardware constraints and firmware development processes. 

• Experience with cloud platforms (AWS, Azure, GCP) for data storage and model training. 

• Familiarity with data labeling and annotation tools/processes. 

• AI Security/Compliance certification is an asset. 

Location: This position is based in Woodbridge, Ontario, Canada.