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!
Top Skills
Huggingface
Jax
Python
PyTorch
TensorFlow
Similar Jobs
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
As a Senior Staff Machine Learning Engineer, you'll develop AI/ML solutions, collaborate cross-functionally, and enhance customer experience through conversational AI and data processing.
Top Skills:
AICloud-Based SolutionsData Processing PipelinesLarge Language ModelsMachine Learning
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
The Principal Machine Learning Engineer will build AI/ML solutions, collaborate with engineers, ensure product security and compliance with AI regulations, and drive architectural decisions for enterprise services.
Top Skills:
AICursorGoKubernetesLlmMlPythonWindsurf
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
The Research Staff Machine Learning Engineer will focus on scalable model training for speech technologies, design internal tools, and innovate data strategies.
Top Skills:
Audio ProcessingDockerKubernetesMachine LearningMlflowPrefectSpeech RecognitionText To Speech
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
