As a Machine Learning Engineer on the research team, you will bring AI into the physical world and thrive at the intersection of theory and practical application. You will work with researchers, engineers, and customers to build, scale, and deploy intelligent systems.
The Product AI team uses AI/ML to directly support Tidal's mission to be the first consideration for an artist when they want to share their music. You will develop new AI/ML systems that power Tidal's homepage including search, recommendations, UX and playlists. You will also build production systems that personalize the listener's experience.
Design and implement scalable ML and deep learning models using PyTorch, TensorFlow, Scikit-learn, and other modern frameworks. Build and optimize RAG pipelines using models like GPT, Claude, or other LLMs integrated with document retrieval systems. Develop production-ready ML applications in cloud environments (AWS, SageMaker, Databricks, etc.).
As an MLE II / AI Engineer in NextGen, you’ll be part of a cross-functional team inventing new AI-powered listening experiences. You’ll explore emerging AI capabilities, prototype end-to-end products, and help bring new features from concept to launch to millions of users. This is a fast-paced, high-growth role ideal for someone early in their career who is eager to learn by building.
We are seeking a talented and experienced Sr ML Engineer to help us optimize training, inference, and Retrieval-Augmented Generation (RAG) pipelines for high-performance AI applications. You will lead the development of connectors to open-source frameworks for data streaming and inference optimizations. Collaborating closely with software developers, product teams, and partners, you will lead experiments with state-of-the-art models using open-source tools and cloud platforms.
We are seeking an experienced Senior Staff Machine Learning Engineer to join our dynamic team and take a leading role in developing cutting-edge machine learning systems that drive business growth. As a key technical contributor, you will drive the development, deployment, and scalability of machine learning models in a production environment, ensuring they deliver value and performance at scale. You will collaborate closely with data scientists, product teams and engineers to implement state-of-the-art solutions that power our products and services through continuous innovation.
The Auto Labeling team at Stack develops large ML models to generate high-quality labeled data, essential for training and evaluating Stack's onboard perception models. The models leverage state-of-the-art multi-sensor fusion techniques, integrating data from lidars, cameras, radars, and IMUs. Significant design contributions and collaboration with onboard and offboard consumers of labeled data are expected.
We're seeking a Machine Learning Engineer specializing in Large Language Model systems engineering and applied research, responsible for implementing and maintaining LLM-based system components and contributing to research initiatives in educational and research domains, working on production-grade LLM systems that serve research institutions and educational organizations.
This year the Content Management & Distribution team is on a mission to revolutionise their content management experience using AI. As the first MLE in the team you will lay the technical foundations for our ML stack, set coding and experimentation standards, and deliver high‑impact models that power content discovery and personalisation across Canva.
As a Machine Learning Engineer, you will play a crucial role in developing cutting-edge machine learning solutions to improve the automotive shopping experience for consumers. You will work on a range of engaging projects aimed at optimizing pricing models, recommendation systems, and shopper segmentation. Collaborate with stakeholders to fuse ideas from business issues to machine learning solutions. Solve moderately complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.