R&D AI Software Engineer / End-to-End Machine Learning Engineer / RAG and LLM

About Pathway

At Pathway we are shaking the foundations of artificial intelligence by introducing the world’s first post-transformer model that adapts and thinks just like humans. 

Our breakthrough architecture outperforms Transformer and provides the enterprise with full visibility into how the model works. Combining the foundational model with the fastest data processing engine on the market, Pathway enables enterprises to move beyond incremental optimization and toward truly contextualized, experience-driven intelligence. We are trusted by organizations such as NATO, La Poste, and Formula 1 racing teams.

Pathway is led by co-founder & CEO Zuzanna Stamirowska, a complexity scientist who created a team consisting of AI pioneers, including CTO Jan Chorowski who was the first person to apply Attention to speech and worked with Nobel laureate Geoff Hinton at Google Brain, as well as CSO Adrian Kosowski, a leading computer scientist and quantum physicist who obtained his PhD at the age of 20. 

The company is backed by leading investors and advisors, including Lukasz Kaiser, co-author of the Transformer (“the T” in ChatGPT) and a key researcher behind OpenAI’s reasoning models. Pathway is headquartered in Palo Alto, California.

The Opportunity

We are currently searching for 2 ML/AI Engineers with a solid software engineering backbone who are able to prototype, evaluate, improve, and productionize end-to-end Machine Learning projects with enterprise data.

For representative examples of the type of projects you would be expected to create or deliver, see our AI pipelines templates.

If you would consider it would be fun to create a hybrid Vector/Graph index that beats the state of the art on a RAG benchmark, to deliver a working AI pipeline to a client in a critical industry, or to pre-process datasets in a way which would boost LLM accuracy in inference & training - this is the job for you!

You Will

• help design experimental end-to-end ML/AI pipelines
• contribute to addressing new use cases, beyond state of the art
• improve/adapt AI pipelines for production, working directly with client data (often live data streams)
• invent ways to pre-process data sources and perform tweaks (reranking, model paramater configuration...) for optimal performance of AI pipelines.
• design benchmark tasks and perform experiments.
• build unit tests and implement model monitoring.
• contribute high-quality production code to our developer frameworks, used by thousands of developers.
• help to pre-process data sets for LLM training.
  

The results of your work will play a crucial role in the success of both our developer offering and client delivery.