Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.
About Ritual
About the roleRitual is building a sovereign, execution layer for AI, with our private testnet already live and running. The Ritual chain is the first blockchain custom-built to support AI-native operations, designed from the ground up to enable a new class of applications at the intersection of crypto and AI. Our first product, Infernet, is pioneering new ground as the first solution to enable developers to access AI models both on-chain via smart contracts and off-chain, demonstrating our commitment to bridging these transformative technologies.
We are looking for a talented and motivated Machine Learning Product Engineer to join our team. In this role, you will work on a variety of projects related to applied machine learning, including working with the product team on automating Data ETL pipelines, deploying machine learning models, and shipping customer-facing products.
- Scale up model inference and running predictions at scale on cutting-edge models
- Work end to end to connect ML models to human interfaces (e.g. APIs, browsers, and applications)
- Designing and implementing large-scale data and ML pipelines through a full end-to-end product development lifecycle
- Collaborate with a cross-functional team of engineers, researchers, product managers, designers, and operations teammates to create cutting-edge products
- Experience as a software engineer
- Experience building and serving machine learning models
- Familiarity with Python and related ML frameworks such as PyTorch, Tensorflow, Jax, and other open-source stacks such as HuggingFace
- Ability to reason through machine learning system tradeoffs
- A high level of end-to-end ownership and self-direction
- Familiarity with basic machine learning system stacks e.g. TinyML, Triton, CUDA, ROCm, Exo, MLIR, Halide, etc
- Familiarity with DataOps, MLOps, and ML orchestration pipelines
- Understanding of modern ML architectures and intuition for inference performance tradeoffs
- Experience or interest in working on open-source ML products
- Interest in building tech aligned with user privacy, computational integrity, and/or censorship resistance
- Experience at fast-growing companies or startups
- Join a passionate group of engineers, researchers, and operators on a mission to build the next generation of AI infrastructure
- Highly competitive compensation package, including annual discretionary bonus & optimized tax structure compared to the vast majority of web3 startups
- Top 1% of benefits across the web3 startup space
- 100% of premiums covered on highest quality healthcare
- Aggressive company 401k match
- Fully remote and/or hybrid, up to you!
- Participate in virtual and in-person events
- Much much more!
Ritual.net Toronto, Ontario, CAN Office
Toronto, Canada
Similar Jobs
Fintech • Financial Services
Design and develop ML platforms, frameworks, and services; collaborate with data scientists on algorithms and simulations; build model hosting and integration services; create data pipelines and monitoring tools for large datasets and ML applications.
Top Skills:
AngularApache HiveAWSAzureC/C++CaffeHadoopHbaseJavaKafkaKerasMS OfficePigPythonReactScalaScikit-LearnSparkTensorFlow
Big Data • Fintech • Mobile • Payments • Financial Services
Build and iterate underwriting ML models for real-time transaction decisions. Develop feature pipelines and training datasets, prototype and evaluate models, productionize into batch or real-time systems, and instrument model/data health, retraining, and monitoring. Collaborate with engineering, risk, product, and ML platform teams to deploy robust, low-latency solutions with appropriate risk controls.
Top Skills:
AirflowCatboostClaude CodeCursorDaskKubeflowLightgbmMlflowPythonPyTorchRaySparkXgboost
Artificial Intelligence
Design, train, and fine-tune state-of-the-art language models and AI agents (with retrieval augmentation). Build efficient, scalable training and inference systems, stay current with ML research, and collaborate with product and design to deliver impactful applications.
Top Skills:
Ai AgentsLanguage ModelsMl Inference SystemsMl Training SystemsPyTorchRetrieval-Augmented Models (Rag)Transformers
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.
