At a Glance
- Tasks: Join a dynamic team to ensure top-notch quality for cutting-edge ML systems.
- Company: Autodesk, a leader in innovative software solutions with a vibrant culture.
- Benefits: Competitive salary, remote work options, and a comprehensive benefits package.
- Other info: Collaborate globally and enjoy excellent career growth opportunities in a hybrid-first environment.
- Why this job: Make a real impact by shaping the future of technology and innovation.
- Qualifications: 7+ years in software engineering or QA, strong Python skills, and a passion for ML.
The predicted salary is between 63000 - 77000 £ per year.
As a Senior Machine Learning QA Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning Engineers and software engineers to define and uphold quality standards for ML systems. You are a quality-focused engineer who is passionate about reliable, repeatable evaluation of ML models and data. Your skills span test strategy, automation, and a little MLOps, with a strong software engineering base. You are excited to collaborate across research and product to ship ML capabilities with clear quality gates. You are comfortable working at the intersection of research and product and are 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
- Evaluating CAD RL model outputs for geometric validity or policy stability
- Defining structured rubrics that translate qualitative findings into measurable evaluation gates
- Testing 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
Minimum Qualifications
- 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
Preferred Qualifications
- Experience with data validation tooling (e.g., Great Expectations) or labeling workflows
- Familiarity with ML frameworks (e.g., PyTorch, TensorFlow)
- Experience with CI/CD tools and processes
- Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)
- Familiarity with MLOps practices (model monitoring, drift, deployment checks)
- Experience with ML evaluation methods, metrics, and benchmarking
- Passion for learning new technologies and improving existing systems
- Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform)
- Experience testing ML services in production environments
- Knowledge of experiment tracking tools (e.g., Comet, MLflow, Weights & Biases)
The Ideal Candidate
- You demonstrate initiative to provide solutions and to learn and develop new technologies
- Comfortable building QA systems from scratch and writing maintainable automation
- You enjoy learning and collaborating across global locations
- You are comfortable working in newly forming ambiguous areas
- You are comfortable building scalable and maintainable systems that will be relied on by others
- You can communicate well with others
Senior Machine Learning Test Engineer United Kingdom in Birmingham employer: Autodesk
At Autodesk, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. As a Senior QA Automation Engineer in Sheffield, you will benefit from extensive professional development opportunities, a supportive team environment, and the chance to work on cutting-edge AI applications that make a real impact. Our commitment to employee well-being and growth, combined with our focus on quality and excellence, makes Autodesk an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Test Engineer United Kingdom in Birmingham
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Autodesk or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Autodesk.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Autodesk.
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Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Autodesk that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Machine Learning Test Engineer United Kingdom in Birmingham
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Autodesk.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Autodesk and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Autodesk
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Autodesk uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
