| Global Market for QA

Markets are changing rapidly, and there is a demand for quick software releases. Agile development has become mainstream; on a global scale, 92% of developer teams adopt agile development, 71% of which aim to release at least once a week. With such a rapid cycle, manual verification is too time-consuming, and there is an urgent need for automation. Our services can solve these critical challenges and make our clients a competitive advantage in software development. QA’s global budget is said to reach over $1 trillion. We are rapidly expanding our service reach internationally to win this vast global market.

| About Us

Autify, Inc. is a San Francisco-based startup that was founded by the first Japanese team to graduate from Alchemist Accelerator, one of the top accelerators in the US. With the mission to empower people’s creativity through technology, we have been offering an AI-powered automation platform aiming to eliminate the test phase.

Since 2019, we’ve been providing our AI-powered nocode test automation product and have grown the team to 100+. Our next move is to double down on GenAI. As we have been investing in AI and helping customers’ software quality since 2019, we know how to best utilize GenAI in software QA. With that, we have recently launched our new product, Genesis, a GenAI agent for software quality assurance.

| Global Market for QA

Markets are changing rapidly, and there is a demand for quick software releases. Agile development has become mainstream; on a global scale, 92% of developer teams adopt agile development, 71% of which aim to release at least once a week. With such a rapid cycle, manual verification is too time-consuming, and there is an urgent need for automation. Our services can solve these critical challenges and make our clients a competitive advantage in software development. QA’s global budget is said to reach over $1 trillion. We are rapidly expanding our service reach internationally to win this vast global market.

| About Us

Autify, Inc. is a San Francisco-based startup that was founded by the first Japanese team to graduate from Alchemist Accelerator, one of the top accelerators in the US. With the mission to empower people’s creativity through technology, we have been offering an AI-powered automation platform aiming to eliminate the test phase.

Since 2019, we’ve been providing our AI-powered nocode test automation product and have grown the team to 100+. Our next move is to double down on GenAI. As we have been investing in AI and helping customers’ software quality since 2019, we know how to best utilize GenAI in software QA. With that, we have recently launched our new product, Genesis, a GenAI agent for software quality assurance.

| About This Role

Job Purpose

We are expanding our team to take our AI capabilities to the next level. As an AI Researcher, your mission will be to push the boundaries of how our platform leverages AI—through smarter use of context in agents, optimization and fine-tuning of models (including small and local models like SML), and innovations to support both cloud-based and local execution environments.

You will take ownership of your own research and development projects, from ideation to implementation. While we align on core product capabilities and minimum requirements through shared discussions, execution is driven by individual initiative. This is a hands-on role where you’ll be expected to deliver quick PoCs that can later evolve into integrated product features.

Responsibilities

Research, prototype, and implement enhancements to our AI agent systems, especially around contextual understanding and adaptive behavior.

Design and train custom models for local execution, including small language models (SML) and hybrid architectures.

Optimize performance and memory usage for AI features deployed on edge or desktop environments.

Collaborate with cross-functional teams to explore new use cases for intelligent agents in our product. Including the best way to leverage large dataset to optimize context and prompt inputs

Evaluate and integrate advancements in LLMs, multi-agent systems, and few-shot / retrieval-augmented techniques.

Maintain awareness of the latest developments in AI and share insights that could influence product direction.

Contribute to the development of internal tools for experimentation and model deployment.

Required Qualifications

5+ years of experience in AI/ML research or applied machine learning roles, ideally in product-focused teams.

Deep understanding of modern LLMs, transformers, and techniques for contextual embedding, instruction tuning, or retrieval-augmented generation (RAG or other approaches).

Experience customizing or distilling large models (e.g., using LoRA, quantization, pruning).

Proficiency with Python and popular ML frameworks (e.g., PyTorch, Hugging Face Transformers).

Solid engineering background, capable of building production-quality prototypes and deploying ML systems in real-world environments.

Familiarity with local inference techniques, edge ML deployments, or multi-modal agent systems.

Ability to communicate technical concepts clearly in English, both written and spoken.

Nice-to-Have

Experience working with small or embedded models (e.g., SML, TinyML, LLaMA variants).

Background in knowledge graphs, few-shot learning, or autonomous agents.

Familiarity with privacy-preserving techniques in AI (e.g., federated learning, differential privacy).

Contributions to open-source AI projects.

Experience with real-time or desktop-based inference environments (e.g., using ONNX, TensorRT, or similar).

Desired personality traits

Product-minded: You think about how research improves user experience and drives impact.

Curious and self-driven: You enjoy exploring new approaches and learning independently.

Collaborative and open: You value feedback and diverse perspectives.

Pragmatic: You balance cutting-edge techniques with practical feasibility.

A solution-first mindset, where any challenges and complex pushback are transformed into opportunities for delivery

Selection Process

1. HR Interview: 45 mins

2. Ideation and simple PoC or review of personal projects

3. Technical Interview: 60 mins

4. Manager Interview: 45 mins

| About the Engineering Team

Our Team

Autify's engineering team is international, with more than half of the engineers being foreign nationals and all developers being English speakers. We have a good culture where members respect each other's backgrounds. Since we have two products, Autify for Web and Autify for Mobile, our development engineers are divided into two teams corresponding to each product. We have about 30 front-end, back-end, and technical support engineers who work closely with engineering managers, product managers, QA managers, designers, and machine learning engineers. The product manager is in charge of the general roadmap. The product manager develops a rough roadmap and works with the engineers and designers on the details of each feature and bug fixes before implementation. Depending on the size of the feature, we appoint a feature lead from among the engineers to be in charge of the project and give them the discretion to make technical decisions.

Our Development Process

We create a ticket about what kind of function we will develop. In some cases, the product owner creates it based on user feedback; in other cases, each team creates bugs and investigation requests directly.

The development cycle consists of one Sprint, which takes two weeks. Development tasks are assigned during the planning stage on the first day of the Sprint, and we hold a daily standup meeting to check the overall progress and any problems. (If there is a time difference, it is done at lunchtime).

We review code on GitHub. After the review, the merged branches are automatically deployed to the staging environment, and E2E tests are performed (which Autify does itself).

After testing on the integrated branch, it's deployed to the production environment. Deployment is done several times a week as needed. We also hold sprint ceremonies like Sprint planning, feature refinement and sprint retrospective sessions. The developer will demonstrate the developed function to all employees at the end of the Sprint in the Sprint Demo.

Tech Stack

- Backend: Ruby, Ruby on Rails, Go

- Frontend: JavaScript, TypeScript, React, Redux, Styled Components

- Machine learning: Python, PyTorch, Kubernetes, GPT-4

- Database: PostgreSQL, Redis

- Test: Appium, Selenium, WebdriverIO, Puppeteer

- Infrastructure: AWS, Docker, Terraform, Packer, MacStadium, GoogleCloud

- Monitoring: Datadog, New Relic, Sentry

- CI/CD: CircleCI, GitHub Actions

- Source code management: GitHub

- Project management: Jira

- Misc.: G Suite, Slack, Notion, Gather, Zoom, Miro, 1Password, Mixmax, Calendly, etc.

| Employment Conditions

Employment Status

- Permanent employee (Full-time)

- Probation period: 6 months after joining the company (conditions are the same as permanent employment)

Work Location

- Tokyo office or Remote in Japan

Work Hours

- Full flextime time

Note: The determination of working hours (start and end times) must be made to the extent that one's own duties (including guidance and supervision of subordinates) are properly performed and that there are no obstacles to work in terms of coordination and communication with other employees.

Bonus

- Twice a year

Holidays/PTO

- Complete a five-day workweek system (National holidays, Year-end and New Year holidays, etc.)

- Unlimited paid time off

Benefits

- Equipped with various social insurance

- Regular health checkups

- Stock option

- A laptop PC will be rented when joining the company

- Remote work allowance

- English learning support

- Skill-up support

- Visa sponsorship

- Relocation bonus

- Relocation housing support

| Resources

- Autify Genesis

https://autify.jp/products/genesis

- Autify No-code

https://nocode.autify.com/

- Career

https://autify.com/careers

- Blogs

https://autify.com/blogs/

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