Senior Python ML Engineer

About Us:

We are the most dependable AI order taker for drive-thrus—designed to scale effortlessly. Our solution is purpose-built for high-volume QSRs, helping brands consistently deliver faster, more accurate service with over 93% order completion and 96% accuracy.

Brands maintain full control over scripts, upselling strategies, and voice customization, enabling precise optimization of drive-thru operations across all locations. Meanwhile, franchisees enjoy the flexibility to update menus, manage LTOs, and tailor regional promotions.

With built-in labor optimization, we help reduce employee stress and turnover—saving hours of labor each day while enhancing the guest experience.

About the role:

Our backend is developed all in Python running in the cloud over k8s. It's not a typical backend interacting with a UI frontend, handling audio streams in real-time. Our systems integrate with a large number of third party services. Because of the myriad of challenges and the fast pace of a startup, each team member gets to experience a lot of professional growth and ownership.

In this role, you will:

• Design, implement and integrate configurable conversational pipelines for
  various order-taking scenarios.
• Work hand in hand with the ML engineers and integrate Generative AI based pipelines into production.
• Triage and analyze production AI performance issues.
• Own and maintain data analysis pipelines and tools.
• Implement and maintain infrastructure for automated tests of all AI related pipelines ensuring stability and accuracy.

Qualifications:

• 6+ years experience in Python Strong backend development and software architecture skills
• Proficient with AsyncIO
• The 2+ years experience of being a tech lead is a must.
• Redis (Experience writing custom LUA scripts to alter something or adding some additional functionality to the Redis).
• Experience with conversational AI applications.
• Integration with third party services - very relevant, but we need to understand, what services? What APIs? Did the candidate use an already existing library? (which is 100% easier), or did he write the protocols?
• Experience with Data Parsing
• PostgreSQL
• Integrations tests - experience with integration tests is good, although they are kind of built in, in the testing utilities that FAST API provides. If the candidates wrote unit tests, it would be interesting to check what exactly they have been testing in terms of smaller functions and what did they write unit tests for?