ML Engineer training diffusion models for Hapiko’s voice - activated Stickerbox, which turns kids’ spoken ideas into stickers. Bringing Spin Master characters into production safely and on - model.
About the role
- Senior Machine Learning Engineer productizing scalable deep learning models for Movable Ink’s content personalization and AI decisioning platform. Advancing ML infrastructure, inference performance, monitoring, and automated testing.
Responsibilities
- Deploy robust, commercial-grade AI products that redefine client expectations.
- Seamlessly integrate breakthrough innovations into the core AI models suite.
- Engineer high-performance, scalable ML systems with reliable operation under pressure.
- Elevate the ML Platform with standards for monitoring, orchestration, and automated testing.
- Drive product adoption and client satisfaction through AI-driven insights.
- Ship high-impact AI models that translate into business growth.
Requirements
- 5+ years of experience in AI/ML development, focused on architecting deep learning systems and sophisticated model pipelines
- Master’s degree or higher in Computer Science, Mathematics, Engineering, or a related technical field
- Proven track record of productizing breakthrough AI research into commercial-grade deep learning models
- Deep expertise in neural network architectures, including transformer architecture, computer vision, natural language processing, and multimodal learning
- Experience optimizing and fine-tuning models for high-performance inference at scale
- Advanced proficiency in PyTorch or TensorFlow, including implementing and adapting state-of-the-art research papers
- Proficiency in Python and experience with machine learning libraries and frameworks such as scikit-learn and XGBoost
- Experience with large-scale data processing frameworks such as Spark and cloud computing platforms such as Google Cloud Platform is desirable
- Experience designing and maintaining production ML systems at scale, including workflow orchestration, artifact versioning, online/offline evaluation, performance monitoring, and A/B testing
- Strong background in statistical modeling and predictive analytics for recommender systems and propensity scoring
- Strategic understanding of the AI model lifecycle from discovery and experimentation through production deployment and evaluation
- Strong technical leadership skills, including guiding and mentoring junior engineers
- Ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams
- Ability to work effectively in a fast-paced, deadline-driven environment and manage multiple priorities
- Detail-oriented with a strong commitment to delivering high-quality solutions
- Eagerness to continuously learn and stay current with advancements in AI and related technologies
Benefits
- Additional bonus depending on the position ultimately offered
- A full range of medical, financial, and/or other benefits
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