Senior ML Platform Engineer

Résumé du poste

You will own the architecture and performance of the machine learning pipeline for a global consumer hardware product. This includes managing end-to-end latency, model deployment, and infrastructure scalability to ensure a high-quality user experience.

Détails du poste

Please Note: If you are a current Spin Master employee with access to Workday, apply to this job via the Workday application. Are you a kid at heart looking to build a career with a leading global children's toy, entertainment and digital gaming company? At Spin Master, our unwavering commitment to open mindedness, integrity and innovation is a great part of what has made us an industry leader. How do we stay ahead of the pack? By hiring the best and brightest minds—and that’s why we want you! Job Description: Hapiko and the Stickerbox Story Hapiko, a new part of the Spin Master family, is the creator of Stickerbox, an AI sticker printer for kids. A child holds a button, says "a unicorn riding a slice of pizza through space," and seconds later, a physical sticker prints out. This is powered by a proprietary generation pipeline that turns a child's idea into safe, fun, printed art in just a few seconds. What will you work on? You aren’t just one of a dozen ML engineers lost in a Big Tech department. You will own the architecture and performance of the machine learning pipeline that powers Stickerbox, scaling this technology to support a global product launch. This role is designed for a builder who wants to learn exactly how to launch and scale a physical AI product for kids from the ground up. You will make the foundational architectural decisions and translate product requirements into reality. This is a hybrid role, 4 days per week out of our Toronto office. How will you create impact? Own end-to-end latency from a kid's voiced input to a physical printed sticker, and the profiling to eliminate every bottleneck Design and manage model deployment, versioning, and rollback strategies for a fleet of consumer hardware devices Optimize batching, caching, and GPU utilization across image generation, speech recognition, and character models to keep the experience fast and affordable Conduct build-vs-buy analysis for hosting and inference architecture and lead any resulting migrations Design and maintain serving-side enforcement of product safety, kid-safe compliance, and automated character-fidelity checks Manage the queues, autoscaling, observability, and release engineering that supports the ML generation path What are your skills and experience? Experience deploying and operating diffusion or similar generative ML models in production with real latency constraints Experience profiling a generation path to optimize for performance and cost End-to-end production ownership experience, including deployment, capacity planning, observability, and on-call support Advanced knowledge of ML infrastructure, inference systems, and production software architecture Experience translating product requirements into scalable technical solutions and roadmaps Experience with consumer hardware, on-device/edge inference, ASR, or child-directed digital products is a strong plus #LI-Hybrid #LI-HM1 The anticipated pay range for candidates who will work in Toronto is $145,000 to $193,000 Per Annum. The offered pay to a successful candidate will be dependent on several factors that may include but are not limited to years of experience within the job, years of experience within the required industry, education, etc. Spin Master Inc. is a multi-state employer, and this salary range may not reflect positions that work only in other states. This job posting is tied to an open vacancy. This job posting is tied to an open vacancy. What you can expect from us: Our mission is to Make Life More Fun with a vision to push the boundaries of innovation, creativity, and fun. Growth and Career Opportunities Flexible Work Hours Innovation, Collaboration and Fun Comprehensive Benefits Other fun Perks! What’s it like to work here? Spin Master is a fast-paced, hands-on organization that provides many great opportunities for impactful decision-making; though our challenging start-up atmosphere isn’t for everyone, we have a proven record of opportunities for future advancement and internal transfers for our passionate and results driven team. Everyone is welcome in our sandbox and we are committed to an accessible and inclusive hiring process that provides reasonable accommodation to all applicants. Spin Master strives to create an accessible and inclusive application and selection process and is committed to working with and providing reasonable accommodation to job applicants who may require provisions to participate in the recruitment, selection and/or assessment processes. Should you require an accommodation, please contact our Talent Acquisition team, by email at TAinquiries@spinmaster.com or by phone at 416 364-6002 and we will work with you to meet your accessibility needs. Follow us on Instagram and Twitter @SpinMaster to stay up to date on Spin Master career opportunities. We do appreciate all interest; however only those selected for interview will be contacted.

Ce que vous ferez

You will own the architecture and performance of the machine learning pipeline for a global consumer hardware product. This includes managing end-to-end latency, model deployment, and infrastructure scalability to ensure a high-quality user experience.

Exigences

The role requires extensive experience in deploying and operating generative ML models in production environments with strict latency constraints. Candidates must possess advanced knowledge of ML infrastructure, performance profiling, and the ability to translate product requirements into scalable technical solutions.

Avantages

• Growth and career opportunities • Flexible work hours • Comprehensive benefits • Innovation and collaboration

Compétences indiquées

• Production · Souhaitée
• Technical · Souhaitée
• assessment · Souhaitée
• analysis · Souhaitée
• Collaboration · Souhaitée
• Compliance · Souhaitée
• Decision Making · Souhaitée
• Process · Souhaitée
• Apprentissage automatique · Souhaitée
• Pipeline · Souhaitée
• Workday · Souhaitée
• Flexible · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Machine learning infrastructure
• Inference systems
• Production software architecture
• Diffusion models
• Generative AI
• Latency optimization
• Model deployment
• Capacity planning
• Observability
• GPU utilization
• Edge inference
• ASR
• Release engineering
• Build-vs-buy analysis
• Technical roadmaps
• Build vs Buy Analysis
• Image Generation
• Product Requirements
• Artificial Intelligence
• Decision Making
• Creativity
• Scalability
• Innovation
• Machine Learning
• Safety Standards
• Software Architecture
• Release Engineering
• Software Versioning
• Autoscaling
• Machine Learning Infrastructure

Domaines d’emploi

• Technology
• Software
• Engineering
• Data & Analytics
• Platform Engineer
• Software and Applications Developers and Analysts Not Elsewhere Classified
• Validation Engineers
• Industrial Engineers