Jobs in United Kingdom

Assistant Manager Cell Quality in United Kingdom

32 active opportunities · Updated October 2026

Explore current assistant manager cell quality jobs across United Kingdom. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 London, Europe, United Kingdom· Full-time
✓ Quality checkedCompany trend -100%

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Location: Philippines (APAC region) About the role As a Customer Support Associate (CSA) you will act as the frontline key person, responsible for providing support and assistance to customers who have inquiries or issues with our product or services. The role: Respond to customer inquiries via email, chat, or social media in a timely and professional manner Provide accurate information and support to customers to resolve their issues Identify and escalate complex issues to Tier 2 support when necessary Collaborate with other teams such as technical support specialists, support product specialists, and leadership to resolve customer issues Record and maintain accurate customer information within our CRM systems (Intercom & Salesforce) Meet individual and team performance metrics (KPI’s) such as first response times, first contact resolution rates, and customer satisfaction Continuously improve your own product knowledge and remain up to date with our product, services and processes Provide constructive feedback to the business and leadership team to improve customer support processes and procedures About you : Based in the Philippines High school diploma or equivalent; college or a degree in a related field

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📍 London, Greater London, United Kingdom· Full-time
✓ Quality checkedCompany trend -100%

About the Team OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. About the Role As a member of the training team, you will push the frontier of LLM development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Relevant interests may include areas such as architecture design, long-context and efficient attention, optimization and the science of scaling. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in London. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, prototype and scale up new architectures to improve model intelligence Execute and analyze experiments autonomously and collaboratively Study, debug, and optimize both model performance and computational performance Contribute to training and inference infrastructure You might thrive in this role if you: Have experience landing contributions to major LLM training runs Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion Are motivated by safely deploying LLMs in the real world Are well-versed in the state of the a

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