Location: Remote

About ​U​S

​W​e are a VC backed high-growth startup building software to make access to knowledge and support easy and instant for the Franchising Industry. The software can look through all information stored across operating manuals, file management systems, training videos, chat groups, etc. and provide summarized answers to franchisee operational questions instantly. However, our end goal is to become the universal interface into all elements of our customer’s tech stack: enabling our customers to query their data, launch workflows and run their operations using simple natural language from one place.

​W​e are a forward-thinking company dedicated to fundamentally re-imagining how people across a wide set of industries interact with technology. Our success relies on the effective application of Information Retrieval (IR) and Machine Learning (ML) principles as well as cutting edge work on agentic AI. As a Machine Learning Engineer you will play a crucial role in improving and scaling up our search product as well as helping research and develop our universal interface agentic AI.

Overview of Responsibilities:

The role of the Machine Learning Engineer at the company involves several key responsibilities:
 

• Planning and development of our novel agentic AI that will enable our customers to easily perform work across all elements of the tech stack in an intuitive, reliable and highly efficient manner.
• Building a robust MLOps pipeline to define, track, and evaluate different configurations of the ML/IR system.
• Implementing IR, NLP and LLMOps techniques to improve the accuracy and reliability of our search product.
• Investigation and debugging of failures in our search product: leading to the development of novel techniques.
• Researching how novel business applications beyond search and communications can be unlocked by recent advances in ML technology.

Skill Prerequisites:

• BSc. in Computer Science, Mathematics, or Engineering as equivalent as a minimum.
• Strong proficiency in Python.
• At least 2 years of prior experience in Machine Learning, working on ML/MLOps problems in industry or academia.
• Strong background in probability and statistics relevant to ML.
• Experience with cloud-based frameworks, preferably AWS. 
• Knowledge of the fundamentals of a full stack engineer. Able to create REST APIs, create a basic frontend, work with git etc. 

Nice-to-have Skills:

• Experience working with LLM APIs like OpenAI or Anthropic.
• Work experience in information retrieval: e.g working on search engines
• Familiarity with Natural Language Processing techniques and theory: e.g experience working on different embedding models, using transformers for NLP tasks
• Academic publications in NLP or Machine Learning 
• Familiarity with orchestration software like airflow and Devops tools like docker.

Our Perks:

• Competitive compensation and stock options
• Benefits package
• Three weeks of paid vacation
• Mentorship and guidance from a highly experienced team include ML Engineer veterans and ML PhD with publications in Nature and Science.
• The opportunity to be an integral part of a novel agentic AI application which will reshape how people interact with technology.