Machine Learning Engineer
Job Purpose Since its official release in October 2019, Autify has been implemented by numerous clients, and our client base is continuing to grow. While we provide all the essential functions required in a test automation platform, we continue to receive requests for new functions and improvements. Autify is working on growing the product further by adding new features. Also, we are looking for opportunities beyond the existing Autify services. To expand our product lineup, we are looking for an AI engineer who focuses on prompt engineering to fully utilize the LLMs’ power, and building LLM-powered PoC applications in Python. You will mainly be responsible for developing a new product utilizing machine learning techniques and generative AI from a proof of concept into a releasable product. Responsibilities - Create effective prompts to maximize the quality of the output from LLMs based on the product specifications - Create PoC Web/CLI applications that use LLMs or ML under the hood to validate the feasibility of ideas - Build our machine learning models using data relevant to the software testing if needed - Work with other engineers, designers, and product leads to implement various features while considering performance, security, and reliability - Proactively identify functions that can be improved, and suggest possible solutions in the technical aspects and product-related ideas - Participate in on-call rotations for incident & alert handling
- 2+ years of technical experience with Python and developing APIs with FastAPI and web applications - Over a year of experience in prompting open-source and closed-source LLMs - Has good comprehension and familiarity with CSS and HTML - Up to date with the latest Machine Learning Research especially on LLMs and Prompt Engineering - Experience in building metrics for evaluating various tasks LLMs. - Being able to work in Japan standard time (Working partially in JST can be discussed) - Ability to communicate and work in English
- Over two years of experience in training and customizing deep learning models, especially LLMs - Knowledge of natural language processing and visual recognition - Proficient in the process of analyzing, hypothesizing, and testing - Experience in MLOps - Modern development experience with Agile or Scrum - Experience in E2E test automation with test automation frameworks like Playwright, Cypress, Selenium, Appium, and etc.