About Luminai
Nearly every organization in the world relies on complex manual work to carry out critical internal processes. These are processes that keep the world going — enrolling patients in a hospital, underwriting loans inside a bank, or processing new transactions for an airline. Yet most companies don’t have enough resources to properly automate these tasks and are stuck in manual, decades old way of doing things.
At Luminai, we develop technology to automate long-form organization wide workflows of any complexity easily and safely using AI. Luminai serves some of the world’s most critical organizations in sectors like Healthcare, Finance, and Telecommunication to delegate mission-critical workflows that previously required hands-on human involvement, over to autonomous AI systems. Our approach combines frontier AI development, with a purpose built workflow execution engine to achieve this goal.
We've raised significant amounts of capital (including some un-announced) from many of the best Silicon Valley VCs: General Catalyst, YCombinator, and investors including Kevin Weil (Chief Product Officer at OpenAI), Arash Ferdowsi (co-founder of Dropbox), Katie Stanton (former VP Global Media, Twitter) and CEOs of companies including Flexport, Notion, Front, Ramp and Twitch.
About the role
As a Software Engineer working on AI systems, you will play a foundational role in research, experimentation and rapid improvement of AI systems towards building a capable, reliable AI automation platform. The platform is used by organizations worldwide to deploy and scale executable AI automations in mission critical production environments. You are expected to have a strong proficiency in fundamentals of software engineering, a willingness to pick new concepts as needed and an ability to drive technical projects in ambitious environments.
You might work on
Design experiments and test ideas to optimize key internal AI benchmarks
Design and improve evaluation frameworks to accelerate the speed and direction of experimentation
Train, fine-tune, and optimize machine learning models. Perform rigorous evaluation and testing to ensure model accuracy, generalization, and performance.
Collaborate and contribute on the core product development to deliver higher platform capabilities
Setup up observability and monitoring systems to safety check model behaviour in critical settings
Things we're looking for
Proven track record of shipping high-quality code in challenging projects
Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field
Solid fundamentals in algorithms, data structures, system design
Attention to detail and a first-principals thinking towards real world deployment of intelligent systems.
Bonus Points
Proficiency in C++
Previous experience working with distributed computing systems in production
