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- Tasks: Design and develop high-performance solutions for AI video production.
- Company: Join Synthesia, a pioneering AI video communications platform.
- Benefits: Attractive compensation, private health insurance, and hybrid work options.
- Why this job: Make a real impact in the fast-evolving world of AI and video technology.
- Qualifications: 3+ years in ML engineering with experience in optimizing large models.
- Other info: Be part of a dynamic team driving innovation in video production.
The predicted salary is between 48000 - 72000 £ per year.
Synthesia is on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos.
We are looking for a ML Performance Engineer to join our team of 40+ Researchers and Engineers within the R&D Department. As a ML Performance Engineer, you will contribute to the design and development of high-performance solutions and own one or more projects for computationally optimizing large-scale model training and inference pipelines.
Your responsibilities will include:
- Evaluating, profiling, and optimizing compute resource usage for cost and time efficiency at training and inference times.
- Developing customized efficient solutions for inference pipelines and introducing or enhancing tooling for achieving optimal computational performance.
- Driving the adoption of best practices for large-model training, including checkpointing, gradient accumulation, and memory optimization.
- Introducing or enhancing tooling for distributed training, performance monitoring, and logging.
- Designing and implementing techniques for model parallelism, data parallelism, and mixed-precision training.
- Keeping updated on the latest research in model compression and advanced optimization methods.
To be successful in this role, you should be a ML engineer passionate about high-performance computing, with a background in Computer Science/Engineering and 3+ years of industry experience. You should have experience optimizing large models, developing CUDA/Triton kernels, and working with DL compilers.
We offer attractive compensation, private health insurance, hybrid work setting, and opportunities for career growth. If you are interested in working for a company that is impacting businesses at a rapid pace across the globe, please apply.
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Senior Machine Learning Engineer - AI & GPU Performance employer: Synthesia
Contact Detail:
Synthesia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - AI & GPU Performance
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already at Synthesia. A friendly chat can open doors and give you insider info on what they're really looking for.
✨Tip Number 2
Show off your skills! If you've got projects or contributions that highlight your expertise in ML performance, make sure to showcase them. A portfolio or GitHub repo can speak volumes about your capabilities.
✨Tip Number 3
Prepare for the interview by diving deep into the latest trends in AI and GPU performance. Being able to discuss recent advancements or share your thoughts on optimisation techniques will definitely impress the team.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our mission at Synthesia.
We think you need these skills to ace Senior Machine Learning Engineer - AI & GPU Performance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your experience in optimizing large models and any relevant projects you've worked on, especially those involving CUDA or Triton.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about high-performance computing and how your background makes you a perfect fit for our team. Don’t forget to mention specific projects or achievements that showcase your expertise.
Showcase Your Projects: If you’ve worked on any relevant projects, make sure to include them in your application. Whether it's a GitHub repo or a personal project, showing us your hands-on experience with model optimization and performance monitoring can really set you apart.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our mission to simplify video production!
How to prepare for a job interview at Synthesia
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially around model optimization and performance. Be ready to discuss your experience with CUDA/Triton kernels and any large-scale model training you've done. This will show that you're not just familiar with the theory but have practical experience too.
✨Showcase Your Projects
Prepare to talk about specific projects where you've optimised compute resource usage or developed efficient inference pipelines. Highlight the challenges you faced and how you overcame them. This gives the interviewers a clear picture of your problem-solving skills and hands-on experience.
✨Stay Current
Keep yourself updated on the latest trends in model compression and advanced optimisation methods. Mention any recent research or tools you've come across that could benefit their work. This shows your passion for the field and your commitment to continuous learning.
✨Ask Smart Questions
Prepare thoughtful questions about their current projects or challenges they face in ML performance. This not only demonstrates your interest in the role but also gives you insight into whether this is the right fit for you. Plus, it shows that you’re proactive and engaged!