At a Glance
- Tasks: Collaborate on innovative ML projects and build features that empower creativity.
- Company: Join Autodesk, a leader in design software impacting the world.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with global collaboration and career advancement.
- Why this job: Make a real difference by working with cutting-edge AI technology.
- Qualifications: 3+ years in machine learning and strong coding skills required.
The predicted salary is between 60000 - 80000 € per year.
The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world. As a Machine Learning Engineer at Autodesk Research, you will work side‑by‑side with world‑class researchers and engineers to build new ML‑powered product features to help our customers imagine, design, and make a better world. You are a software engineer who is passionate about solving problems and building things. You are excited to collaborate with AI researchers to implement generative AI features in Autodesk products. You will report to a research manager in the Research Engineering organization of Autodesk Research. This role can be based at either our offices in London, UK or Toronto, Canada, working in a hybrid working model.
Responsibilities:
- Collaborate on projects at the intersection of research and product with a diverse, global team of researchers and engineers.
- Support research through the construction of ML pipelines, prototypes, and reusable, testable code.
- Process data and analyze feature extractions.
- Analyze errors and provide solutions to problems.
- Present results to collaborators and leadership.
Minimum Qualifications:
- BSc or MSc in Computer Science, or equivalent industry experience.
- 3+ years of machine learning experience.
- Experience scaling machine learning training and data pipelines.
- Experience with computational geometry and geometric methods including mesh or B-Rep models.
- Experience with version control, reproducibility, and deploying machine learning models.
- Experience with data modeling, architecture, and processing using varied data representations including 2D and 3D geometry.
- Experience with cloud services and architectures (e.g. AWS, Azure).
- Proficiency with modern deep learning libraries and frameworks (PyTorch, HuggingFace, Ray).
- Excellent written documentation skills to document code, architectures, and experiments.
Preferred Qualifications:
- Experience working with distributed systems.
- Knowledge of the design, manufacturing, AEC, or media & entertainment industries.
- Experience with Autodesk or similar products (CAD, CAE, CAM, etc.).
Machine Learning Engineer (3D Geometry/Multi-Modal) employer: Merantix
At Autodesk, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters creativity and innovation. As a Machine Learning Engineer, you will have the opportunity to collaborate with leading experts in a hybrid working environment, while benefiting from continuous professional development and a commitment to work-life balance. Our London and Toronto offices provide a vibrant atmosphere where your contributions will help shape the future of design and technology, making a meaningful impact on industries worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (3D Geometry/Multi-Modal)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Autodesk or similar companies. Use LinkedIn to connect and engage with them; you never know who might have a lead on your dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving 3D geometry or multi-modal data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Remember, they want to see how you think and approach problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Autodesk team. Let’s get you that Machine Learning Engineer role!
We think you need these skills to ace Machine Learning Engineer (3D Geometry/Multi-Modal)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with ML pipelines, computational geometry, and any relevant projects that showcase your skills. We want to see how you can contribute to our team!
Showcase Your Projects:Include a section in your application where you showcase your projects, especially those involving generative AI or 3D geometry. This gives us a glimpse of your hands-on experience and problem-solving abilities.
Be Clear and Concise:When writing your cover letter, be clear and concise about why you're a great fit for the role. Use specific examples from your past work to illustrate your points. We appreciate straightforward communication!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Autodesk!
How to prepare for a job interview at Merantix
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially around 3D geometry and multi-modal data. Be ready to discuss your past projects and how you've tackled challenges in scaling ML pipelines or working with geometric methods.
✨Show Your Collaborative Spirit
Since this role involves working closely with researchers and engineers, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve contributed to a team project, especially in a diverse or global setting.
✨Demonstrate Problem-Solving Skills
Expect to face some technical questions or case studies during the interview. Practice articulating your thought process when analysing errors or providing solutions. This will show that you can think critically and adaptively in real-world scenarios.
✨Prepare for Technical Questions
Familiarise yourself with the tools and frameworks mentioned in the job description, like PyTorch and cloud services. You might be asked to solve coding problems or discuss your experience with version control and deploying models, so be ready to dive into the technical details.
