Machine Learning Engineer

Ritual; United States; Remote; USD 120.000 - 190.000; Vollzeit

Benefits dieser Stelle

Remote or hybrid work options

Competitive compensation with annual-b

Premium healthcare

Zusammenfassung

Ritual is seeking a talented Machine Learning Product Engineer to join our team. You will work on applied ML projects, automating data ETL pipelines, deploying models, and shipping customer-facing products.

You will scale inference, connect models to APIs and interfaces, and design end-to-end ML data pipelines within a cross-functional team of engineers, researchers, product managers, designers, and operators.

Qualifikationen

• Experience as a software engineer.
• Experience building and serving machine learning models.
• Familiarity with Python and ML frameworks such as PyTorch, TensorFlow, JAX, and open-source stacks like HuggingFace.
• Ability to reason through machine learning system tradeoffs.
• High level of end-to-end ownership and self-direction.

Aufgaben

• Scale up model inference and run predictions at scale on cutting-edge models.
• Connect ML models to human interfaces (APIs, browsers, applications) end-to-end.
• Design and implement large-scale data and ML pipelines throughout the product lifecycle.
• Collaborate with engineers, researchers, product managers, designers, and operations to create cutting-edge products.

Kenntnisse

Software engineering experience

ML model serving

End-to-end ownership

ML system tradeoffs

Tools

Python

PyTorch

TensorFlow

JAX

HuggingFace

Jobbeschreibung

About Ritual

Ritual is building a sovereign layer for AI. Our first phase, Infernet, is the first product of its kind to enable developers to access models both on-chain via smart contracts and off-chain. Our next phase, the Ritual chain, will be a sovereign layer custom-built to support AI-native operations and enable a new class of applications at the intersection of crypto and AI.

About the role

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

About you

• 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

Extras

• 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

Why join us

• 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!