Team Lead - Performance team

From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read — both at home and at work. Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale. Meet Synthesia. We're 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. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. In 2023, we were one of 7 European companies to reach unicorn status. In February 2024, G2 named us as the fastest growing company in the world. In 2025 we announced our series D funding. In total we’ve raised over $330M in funding from top-tier investors.

About the role

As a Team Lead you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 55,000 businesses. If you are an expert in training Diffusion models for generative AI, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.

What will you be doing?

• Define the technical vision and roadmap for large-scale model training, inference and optimisation.
• Partner with researchers and research teams to identify high-impact initiatives and push the boundaries of model performance.
• Re-implement models in an efficient manner using PyTorch and underlying technologies like Cuda Kernels, Torch compilation techniques.
• Evaluate and optimise compute resource usage (e.g., Hopper GPUs) for cost and time efficiency at training and inference times.
• Drive the adoption of best practices for large-model training, including checkpointing, gradient accumulation, and memory optimisation.
• Introduce or enhance tooling for distributed training, performance monitoring, and logging (e.g., DeepSpeed, PyTorch Distributed).
• Design and implement techniques for model parallelism, data parallelism, and mixed-precision training.
• Keep the team updated on the latest research in model compression (e.g., quantization, pruning) and advanced optimisation methods.
• Lead experiments to validate novel approaches and ensure models remain at the forefront of performance and reliability.
• Manage, mentor, and grow a team of ML optimisation engineers and specialists.
• Provide technical guidance, set goals, review code, and lead by example in writing clean, efficient, maintainable code.

Who are you?

• You are a natural leader, with experience leading teams or high impact projects.
• You have a background in Computer Vision / Computer Science and 3+ years of industry experience (PhD preferred).
• You have worked on optimising large models for over 3 years.
• You have experience with optimising models that were trained on distributed systems.
• You have strong experience in the video space (Diffusion models / GAN’s), preferably in the Avatar or generative video or image domain.
• Experience with Triton, TensorRT, TensorLLM.
• Familiar with distributed training tools like DDP, Deepspeed, Accelerate or similar.
• You are interested in doing research, trying new things and pushing the boundaries.
• You have experience in using most modern frameworks for machine learning and deep learning.
• You have great coding skills in Python, preferably C++ and Cuda.
• You care about writing clean, efficient code.

The good stuff...

• Attractive compensation (salary + stock options + bonus).
• Private Health Insurance in London.
• Hybrid work setting with an office in London.
• 25 days of annual leave + public holidays.
• Work in a great company culture with the option to join regular planning and socials at our hubs.
• A generous referral scheme when you know people that are amazing for us.
• Strong opportunities for your career growth.