Senior ML Infrastructure Engineer — Python & API Focus

A fast-growing open-source startup is building next-generation machine learning infrastructure that redefines how models are represented, transformed, and executed. The goal is to develop a high-performance foundation for AI workloads by separating model architecture from execution strategy — enabling more portable, scalable, and efficient deployments.

We’re looking for an engineer who thrives at the intersection of machine learning, systems design, and developer experience. You’ll help shape the infrastructure’s high-level Python API, integrate it with popular ML frameworks, and build tools that make it easier to compose, debug, and deploy models across a variety of backends.

📍Ankara / On-site

Responsibilities

Design and develop the Python API for model composition and transformation
Build integrations with ML frameworks like PyTorch, TensorFlow, and JAX
Implement tools for model tracing, visualization, and debugging
Write developer documentation, tutorials, and code samples
Design APIs that abstract away execution backends while exposing core ML primitives
Contribute to systems for symbolic and dynamic shape inference

Requirements

3-5 years of Python experience in ML, scientific computing, or systems development
Deep knowledge of at least one major ML framework (e.g., PyTorch, TensorFlow, or JAX)
Familiarity with model graphs, intermediate representations (IRs), or automatic differentiation
Strong understanding of API design and software modularity
Excellent communication skills and ability to collaborate in open-source environments

Nice to Have

Experience building SDKs, APIs, or developer tooling
Contributions to open-source ML systems or infrastructure projects
Familiarity with REST/gRPC APIs or model serving frameworks (e.g., FastAPI, TorchServe)
Knowledge of model versioning, reproducibility, or ML deployment workflows

APPLICATION FORM

Name

First Name

Last Name

How many years have you used Python professionally in machine learning, scientific computing, or infrastructure work?

Which ML frameworks have you worked with extensively? (Select all that apply)

PyTorch

TensorFlow

JAX

Have you designed or maintained Python APIs or SDKs for other developers to use?

Have you worked on tools or libraries for model composition, transformation, or tracing (e.g., TorchScript, TF Graphs, JAX tracing)?

Which developer-facing tools have you worked on? (Check all that apply)

Model debuggers or profilers

Model visualization tools

CLI tools or SDKs

Interactive notebooks / tutorials

Documentation and code examples

I haven’t worked on developer tools yet

Have you contributed to any open-source ML or scientific Python libraries?

Have you worked with any Intermediate Representations (IRs) in ML compilers or model transformation pipelines?

Tell us why you’re interested in this role and what excites you about working on machine learning infrastructure.

GitHub

http://