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
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.
Top Skills:
AICloud ComputingLarge Language ModelsMachine LearningMlops
.png)
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Analyze complex challenges and enhance AI infrastructure through advanced machine learning, while mentoring engineers and developing production-grade systems.
Top Skills:
Apache AirflowDatabricksDeep LearningFlinkGnnsKafkaKinesisLlmsPythonSnowflakeSpark
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
As a Staff Machine Learning Engineer, you'll define technical strategies, design ML models, implement real-time ML pipelines, and deploy systems at scale to enhance Coinbase's operations and user protection.
Top Skills:
DnnsGenaiLlmsMachine LearningTransformers
What you need to know about the Charlotte Tech Scene
Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
