ML Software Engineer: Toolkit & Production Focus

Crowe Advisory LLC; Chicago (IL); On-site; USD 62,000 - 100,000; Full time

Job summary

Crowe Advisory LLC in the United States is seeking a data-science/software-engineering professional to advance machine learning tooling within a dedicated Data Science Team. You will develop libraries and services, move models from prototype to production, and promote reusable Toolkit components.

The role emphasizes autonomy, strong Python skills, Linux, Docker, and cloud experience, with collaboration across data scientists and engineers.

Qualifications

• Programming experience with Python; familiarity with C/C++, Go is a plus.
• Software engineering experience with knowledge of algorithms and data structures; Linux-based and Docker for RESTful APIs.
• Capacity for autonomy; able to manage time between research and tool development.
• Strong communication skills; can adjust discussion from technical to high-level.
• Adaptable to diverse toolkit problems; detail-oriented with maintainable code and tests.
• Enjoy coding and learning new technologies; curiosity about machine learning.
• Outside-field background that brings unique software engineering skills.

Responsibilities

• Execute tasks to achieve the project’s technical vision.
• Support client intake conversations and data exploration for new projects; ongoing feature development and bug fixes.
• Work across the lifecycle to deliver mature ML products in a software release cycle.
• Collaborate with data scientists to move models from prototype to production.
• Promote reuse by developing general tooling and libraries; share code across projects.
• Support teammates through pair programming, code reviews, and knowledge sharing.

Skills

Python

C/C++

Go

Algorithms

Linux

Docker

Cloud

Distributed Systems

CI/CD

Autonomy

Communication

Adaptability

Attention to detail

Coding

ML Curiosity

Diverse background

Job description

Crowe Advisory LLC in the United States is seeking a data-science/software-engineering professional to advance machine learning tooling within a dedicated Data Science Team. You will develop libraries and services, move models from prototype to production, and promote reusable Toolkit components.

The role emphasizes autonomy, strong Python skills, Linux, Docker, and cloud experience, with collaboration across data scientists and engineers.