Team Lead - ML Optimisation team
Team Lead - ML Optimisation team
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Job Description
Who are we
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. If youre reading this and nodding check out our brand video.
Despite the clear preference for video communication and knowledge sharing in the business environment are still dominated by text largely because highquality video production remains complex and challenging to scaleuntil now.
Meet Synthesia
Were 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 highquality videos. Whether its 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. Were trusted by leading brands such as Heineken Zoom Xerox McDonalds and more. Read stories from happy customers and what 1200 people say on G2.
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 weve raised over $330M in funding from toptier investors including NEA Atlassian Ventures WiL PSP Growth and existing investors such as Accel Nvidia Kleiner Perkins GV and top founders and operators including Stripe Datadog Miro Webflow and Facebook.
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 lifelike Synthetic humans through texttovideo. Within the team youll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 55000 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
As our Team Lead for the ML Optimisation team you will define the technical vision and roadmap for largescale model training inference and optimisation. By partnering with researchers and research teams youll identify highimpact initiatives and push the boundaries of model performance. Youll also work on reimplementing models in an efficient manner by using PyTorch and underlying technologies like Cuda Kernels Torch compilation techniques. etc
You will be a handson leader that can inspire the team to go beyond what we are capable of now and lead by example.
This would include:
- Evaluating and optimising compute resource usage (e.g. Hopper GPUs) for cost and time efficiency at training and inference times
- Driving the adoption of best practices for largemodel training including checkpointing gradient accumulation and memory optimisation among others.
- Introducing or enhancing tooling for distributed training performance monitoring and logging (e.g. DeepSpeed PyTorch Distributed).
- Designing and implement techniques for model parallelism data parallelism and mixedprecision training
- Keeping the team updated on the latest research in model compression (e.g. quantization pruning) and advanced optimisation methods.
- Leading experiments to validate novel approaches and ensure models remain at the forefront of performance and reliability.
- Managing mentoring and growing a team of ML optimisation engineers and specialists.
- Providing technical guidance setting goals reviewing code and leading by example in writing clean efficient maintainable code.
Who are you
- You are a natural leader with experience leading teams or high impact projects (beyond POC)
- 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 / GANs) 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 going beyond whats already known.
- 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.
- And 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
Employment Type
Full Time
Key Skills
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