Architect and implement production-ready generative AI and LLM-based solutions within the product suite
Design and develop agentic systems, RAG pipelines, and evaluation workflows to automate tasks and improve reliability
Collaborate with product, design, and engineering teams to turn complex AI concepts into user-facing features
JUPUS is a fast-growing legal tech company in Europe, building the JUPUS platform to improve productivity for law firms. The culture is flat, fully remote, and fast-moving, with direct access to engineering leadership and a focus on practical AI systems.
Build RL environments, agentic systems, LLM pipelines, and evaluation frameworks for real-world AI use cases.
Develop benchmarks and evaluation harnesses to assess model quality across accuracy, safety, latency, and cost.
Conduct fine-tuning and model experiments, deploy self-hosted models, and document reproducible methodologies.
The employer is an organization focused on applied AI research, building practical and reusable AI systems for real-world use cases. It values curiosity, accountability, innovation, collaboration, and continuous learning in a remote environment.
Build production-grade agentic workflows to automate fan issue triage, seller risk monitoring, and marketplace optimization.
Coach non-technical teammates to use AI tools and create their own automations.
Own the full lifecycle of built solutions, from design to production, and scale successes across operations teams.
Gametime makes it easy for people to discover and access live experiences, with platforms supporting over 60,000 events across the US and Canada. They are a mid-sized company focused on reimagining the event ticket industry, with a culture that emphasizes inclusivity and innovation.
Work directly with leading AI labs and enterprises to define research goals and technical requirements.
Build data intelligence systems and implement ML pipelines for data curation, model training, and evaluation.
Develop LLM applications, including multi-agent systems, RAG workflows, and evaluation harnesses.
Our client is a venture-backed AI company building intelligent systems by combining human expertise with machine learning. With over $40 million in funding and a global expert network, they provide critical infrastructure for AI development.