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

ML/AI Engineer

Employment Type: Full-time Location Type: Remote

Position Overview

Pathway is seeking two talented ML/AI Engineers with a strong software engineering foundation to prototype, evaluate, improve, and productionize end-to-end Machine Learning projects using enterprise data. If you are excited by the prospect of creating hybrid Vector/Graph indexes that outperform state-of-the-art on RAG benchmarks, delivering functional AI pipelines to clients in critical industries, or pre-processing datasets to enhance LLM accuracy in inference and training, this role is for you.

About Pathway

Pathway is building live AI systems that think and learn in real time, mirroring human cognitive processes. Our mission is to achieve a deep understanding of how and why Large Language Models (LLMs) function, thereby revolutionizing the way models process information.

Our team comprises leading figures in Artificial Intelligence. Pathway's CTO, Jan Chorowski, has co-authored papers with AI pioneers Geoff Hinton and Yoshua Bengio and was an early adopter of attention mechanisms in speech processing. Our CSO, Adrian Kosowski, earned his PhD in Theoretical Computer Science at the age of 20, making substantial contributions across diverse scientific domains, including AI and quantum information. He also served as a professor and coached competitive programmers at Ecole Polytechnique. The team is further enriched by numerous world-class scientists, competitive programmers, and experienced Silicon Valley executives.

Pathway is backed by strong investors, having raised over $15 million to date, with our latest funding round being our seed round. Our offices are located in Palo Alto, CA, Paris, France, and Wroclaw, Poland.

Responsibilities

• Assist in designing experimental end-to-end ML/AI pipelines.
• Contribute to addressing new use cases that push beyond the current state-of-the-art.
• Improve and adapt AI pipelines for production environments, working directly with client data, which often includes live data streams.
• Innovate methods for pre-processing data sources and implementing adjustments (e.g., reranking, model parameter configuration) to optimize AI pipeline performance.
• Design benchmark tasks and conduct experiments.
• Build unit tests and implement model monitoring.
• Contribute high-quality production code to our developer frameworks, which are utilized by thousands of developers.
• Assist in pre-processing datasets for LLM training.
• Your work will be instrumental in the success of both our developer offering and client delivery.

Requirements

• A degree from a 4+ year university program in Computer Science, with A-grades in foundational courses (e.g., Algorithms, Computational Complexity, Graph Theory) and Machine Learning courses.
• A passion for delivering high-quality, functional code and solutions.
• Proficiency in data handling and engineering innovation, with the ability to build robust systems.
• Hands-on experience with Machine Learning / Data Science using the Python stack (including notebooks).
• Experience with model monitoring, Git, build systems, and CI/CD practices.
• Demonstrated respect for colleagues.
• Curiosity for new technologies, evidenced by active engagement with platforms like Hacker News, arXiv feeds, and AI digests.
• Fluent in English.

Bonus Points

• A successful track record in algorithmic competitions (ICPC / IOI), data science contests (Kaggle), or HuggingFace leaderboards.
• A demonstrable code portfolio.
• A PhD in Computer Science.
• Authorship of a paper at a major Machine Learning conference.
• Enthusiasm for experimenting with new tools within the LLM ecosystem.
• Active participation in the Pathway community or recognition for work in our bootcamps.

Why You Should Apply

• Join an intellectually stimulating work environment.
• Become a technology innovator making a tangible impact, with your code reaching thousands of developers and clients processing billions of data records.
• Be part of a leading team in the AI space.