Machine Learning Engineer - Large Models

Key Skills

Deep Learning, Large Language Models - LLMs, Python Programming, PyTorch, RESTful, Zero-Trust

Job Description

Synthesia is the world’s #1 AI video generation platform. Well, it’s actually a video production studio — in a browser. As in, no cameras or film crews at all. You simply choose an avatar, enter your script in one of 60 languages, and your video is ready in minutes. In Synthesia, you can build personalised on-the-fly videos, give your chatbot a human face or run 24/7 weather channels in different languages, to name just a few of the possibilities.

We believe the future of media is synthetic, and we are on a mission to turn cameras into code and make everyone a creator. To learn more, check out our brand video that explains what we’re doing at Synthesia.

About the role

We are looking for an experienced Machine Learning Engineer,with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

 You will be someone who loves to code and build working systems. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. 

 You will join a group of more than 40 Engineers in the R&D department and will have the opportunity to collaborate with multiple research teams across diverse areas, our R&D research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner.

If you know and love multi-modal LLMs, or have experience fine tuning LLMs with additional modalities - then we would love to talk to you. We will also want to talk to you - if that's what you dream of doing.

What will you be doing?

In this position, you'll join the team to help train LLMs for multi-modal tasks that will help us create emotional, human-like avatars. You will also help us create high quality, production ready code and take ownership of production pipelines. This would include:

• Taking hypotheses, ideas or papers and creating implementations of solutions on the back of these.
• Running experiments on the back of the created implementations to evaluate and verify your hypotheses.
• Enhancing model training and inference optimisation to ensure efficient and accurate results.
• Contributing to a high-quality codebase, developing tests where necessary, and participating in code reviews.
• Helping a team of Research engineers and Scientists to write clean and efficient code, and define best practices.
• Taking ownership of the full ML lifecycle from concept, development, testing, validation to deployment.
• Developing production quality software, our teams work “full stack” with the ability to deliver direct to product and impact the world.
• Optimising for deployment - turning prototypes into working solutions.

Who are you?

• You have a background in Computer Science and 5+ years of relevant experience.
• You have substantial experience working with and training Large Language Models on sizeable clusters, applying this knowledge to practical scenarios.
• You have experience in scaling large models via model parallelism multi-node training and other techniques such as sharding and distillation.
• You demonstrate excellent Python coding skills and have a deep interest in the software development aspect of ML.
• You possess a research-oriented mindset, constantly exploring new techniques and solutions, and are adept at finding what works best in a given scenario.
• And finally..You have excellent verbal and written communication skills and you are passionate about what you do!

Nice to have…

• Advanced expertise in PyTorch, with a deep understanding of its distributed and parallel approaches, as well as the related tools and frameworks.
• Proficiency in state-of-the-art frameworks, with proven experience leveraging these tools to optimise and accelerate ML model training and inference: DeepSpeed, ZeRo, LoRA, Quantization, 3D parallelism, distillation, Bitsandbytes.
• Extensive experience with AWS, including a strong understanding of its various services and how they can be integrated for robust, scalable ML solutions.
• Experience with different modalities (image / audio).

The good stuff...

• You will be compensated well (salary + stock options + bonus)
• You will work in a hybrid setting with an office in London
• You get a cycle to work salary sacrifice scheme to commute to the office
• You get 25 days of annual leave + public holidays
• You will join an established company culture with regular socials and company retreats
• You get 4 weeks paid sabbatical after 4 years at the company + $10,000!!
• You can participate in a generous referral scheme
• You will have huge opportunities for your career growth.