Senior Software Engineer, Applied AI
About The Position
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. 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.
Requirements
- 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.
Nice To Haves
- Proficiency in C++
- Previous experience working with distributed computing systems in production
Responsibilities
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
11-50 employees
