Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

As a Senior Machine Learning QA Engineer in the Research Enablement team, you will work with researchers, Machine Learning Engineers, and software engineers to define and uphold quality standards for ML systems. You are a quality-focused engineer passionate about reliable, repeatable evaluation of ML models and data, with skills spanning test strategy, automation, and MLOps, grounded in software engineering. You will collaborate across research and product to ship ML capabilities with clear quality gates and are comfortable working at the intersection of research and product, competent in using Autodesk CAD software.

Responsibilities

Define ML quality strategy and acceptance criteria across data, model, and system levels
Design and maintain model evaluation suites, metrics, and test datasets
Evaluate CAD RL model outputs for geometric validity or policy stability
Define structured rubrics that translate qualitative findings into measurable evaluation gates
Test ML Models from product side
API Testing
Automate ML QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins)
Create and maintain test harnesses for ML services and APIs
Mentor teams on ML QA best practices and consistent evaluation standards
Build quality gates for training and deployment pipelines (e.g., regression checks, drift detection)
Contribute to multi-team projects and codebases, ensuring code quality and consistency
Participate in code reviews and provide constructive feedback to peers
Document and present findings and ideas across the company

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent experience
7+ years of professional experience in software engineering or QA for ML/AI systems
Strong programming skills in Python, with experience in test automation
Familiarity with popular CAD environments tooling
Proficient in Automation and UAT test suite/framework
Experience designing QA frameworks or platforms used by multiple teams
Excellent problem-solving skills and attention to detail
Strong communication and collaboration skills
Understanding of software architecture and design patterns
Ability to work in an agile development environment

Skills

Python
Test automation
CI/CD (e.g., GitHub Actions, Jenkins)
API Testing
MLOps
Software engineering
Autodesk CAD software
Data validation tooling (e.g., Great Expectations)
Labeling workflows
ML frameworks (e.g., PyTorch, TensorFlow)
Data pipelines
Orchestration tools (e.g., Airflow, Metaflow)
ML evaluation methods
ML metrics
Benchmarking
Cloud providers (e.g., AWS, Azure, Google Cloud Platform)
Experiment tracking tools (e.g., Comet, MLflow, Weights & Biases)

Location

United Kingdom
London
San Francisco
Toronto
Remote

Work Type

Hybrid-first
Remote
In-office
Mix of both

Experience Level

Senior
7+ years of professional experience

Education Level

Bachelor’s degree in Computer Science, Engineering, or equivalent experience

Benefits

Annual cash bonuses
Stock grants
Comprehensive benefits package

About the Company

Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies.
We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it’s at the core of everything we do.
Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all.
Ready to shape the world and your future? Join us!

Equal Opportunity

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging